feat(tui): expose native OpenCode theme

2026-08-02 16:26:14 -04:00 · 2026-07-23 16:35:57 +00:00
1112 changed files with 106322 additions and 78996 deletions
@@ -0,0 +1,7 @@
 ---
 "@opencode-ai/client": patch
 "@opencode-ai/protocol": patch
 "@opencode-ai/cli": patch
 ---
 Expose background-service lifecycle status, preserve one process-held owner through startup and failure, reconnect TUIs without activating replacement, and stop exact service instances gracefully.
@@ -0,0 +1,5 @@
 ---
 "@opencode-ai/cli": patch
 ---
 Expose a TUI plugin slot at the top of the session view.
@@ -0,0 +1,7 @@
 ---
 "@opencode-ai/client": patch
 "@opencode-ai/plugin": patch
 "@opencode-ai/protocol": patch
 ---
 Expose transient, read-only session generation through the HTTP API, generated clients, and V2 plugin session context.
@@ -0,0 +1,5 @@
 ---
 "@opencode-ai/cli": patch
 ---
 Expose a TUI plugin slot above the session composer.
@@ -1,37 +0,0 @@
 name: deploy-www
 on:
  push:
    branches:
      - dev
      - v2
  workflow_dispatch:
 concurrency:
  group: deploy-www-${{ github.ref_name }}
  cancel-in-progress: false
 permissions:
  contents: read
 jobs:
  deploy:
    if: github.repository == 'anomalyco/opencode' && (github.ref_name == 'dev' || github.ref_name == 'v2')
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@f43a0e5ff2bd294095638e18286ca9a3d1956744 # v3.6.0
      - uses: ./.github/actions/setup-bun
      - name: Build
        working-directory: packages/www
        run: bun run build
        env:
          BLUME_ENV: ${{ github.ref_name == 'v2' && 'production' || 'dev' }}
          CLOUDFLARE_ENV: ${{ github.ref_name == 'v2' && 'production' || 'dev' }}
      - name: Deploy
        working-directory: packages/www
        run: bun run deploy
        env:
          CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
@@ -99,7 +99,7 @@ jobs:
      - name: Check generated documentation
        if: runner.os == 'Linux'
-        working-directory: packages/www
+        working-directory: packages/docs
        run: bun run check:generated
  e2e:
@@ -1,68 +0,0 @@
 ---
 name: ideal-pseudocode
 description: Function-by-function refactoring loop driven by ideal pseudocode. Use when the user says "ideal pseudocode", asks to make a function read like its pseudocode, or wants a dense module cleaned up one function at a time.
 ---
 # Ideal Pseudocode
 Clean up one function at a time by writing the pseudocode it _should_ read as, naming every delta between that and the real code, and closing only the gaps the user approves.
 ## Loop
 One function per round. Never touch code before the user picks a direction.
 1. **Pick the target** with the user — usually the next function up or down the call chain from the last round.
 2. **Read the current code** fresh from disk. It may have unsaved or parallel edits; ask before overwriting anything unexpected.
 3. **Distill.** Write the function's ideal pseudocode in a `ts`-fenced code block — TypeScript-flavored for syntax highlighting, but pseudocode: comments over mechanics, one line per idea, every arm of a loop visible as an arm. For a dense or unfamiliar function, first show the _current_ structure as pseudocode, then the ideal.
 4. **Name the deltas.** A numbered list; each delta is one concrete gap: control flow smuggled through combinators, a flag-typed parameter, colliding names, side-effect plumbing drowning a loop body, twin functions differing only by a filter. For each, give an honest cost/benefit and a decisive recommendation — including "leave it" when the density has reasons (state the reasons).
 5. **Verify before proposing.** Any API the proposal builds on (a combinator, schedule, matcher) gets checked against the installed version's source, not memory.
 6. **Get buy-in, then apply.** Minimal edits. Quarantine irreducible ugliness inside a small helper whose name is the pseudocode line it implements. Collapse shallow sibling functions into one deep function only when the distinguishing argument is a domain noun, not a behavior switch.
 7. **Validate.** Typecheck and the focused test suites from the package directory; rerun timing-sensitive tests repeatedly. Flag any semantic change the restructure introduced, even when tests pass.
 8. **Offer the next target** and stop.
 ## Style
 - Keep each round tight: pseudocode block, deltas, recommendation, one question.
 - State mutation belongs in one visible place (usually the loop tail), never spread across error channels or callback closures.
 - Prefer early return and `if` chains for control flow; matchers are for producing values.
 - Compare names against the question each caller is actually asking; rename toward the domain noun.
 ## Example round
 Every round should read like this (abridged from a real one, on an Effect step-runner):
 > `runStep` it is. The ideal pseudocode:
 >
 > ```ts
 > // One logical step: one settled model call, however many attempts it takes.
 > // An attempt can end without settling in two ways:
 > //   transient provider failure -> retry the same call, same assistant message
 > //   compaction rewrote history -> rebuild the request and call again
 > function runStep(session, promotable, step) {
 >   while (true) {
 >     const result = callModel(session, promotable, step)
 >
 >     if (result.completed) return result
 >
 >     if (result.retryable) {
 >       wait(retrySchedule) // exhausted -> publish Step.Failed, fail drain
 >       promotable = none // never re-promote on a second attempt
 >       continue
 >     }
 >
 >     // compaction restarted the step: fresh request from rewritten history
 >     promotable = none
 >     step = result.step
 >   }
 > }
 > ```
 >
 > Comparing against the real thing, three deltas:
 >
 > 1. **The retry arm doesn't live in the loop.** In the pseudocode, retry is just another loop arm. In the real code it's smuggled through the error channel: `Effect.tapError` mutating loop variables via `Effect.sync` closures, then `Effect.retryOrElse` re-running a suspended call. Four mutable variables mutated from three different places — the state flow is invisible unless you already know the trick.
 > 2. **`recoverOverflow: typeof compaction.compact | undefined`** — a function-typed parameter used as a one-shot armed/disarmed flag. The callee already closes over `compaction`; a boolean says what it is.
 > 3. **`assistantMessageID`** exists solely to resume the same durable message across retries — fine, but only legible once the retry arm is visible in the loop.
 >
 > The unifying move for (1): a schedule driver, so a retryable failure becomes a caught value handled in the loop body exactly like the compaction arm. One honest trade: it's more manual than the blessed combinator — but the manual version is the loop the combinator was hiding, and the loop already exists for restarts. Two restart mechanisms, one control structure.
 >
 > Want me to apply it — unified loop, simplified schedule input, boolean `recoverOverflow`?
@@ -1,3 +1,4 @@
 - To regenerate the legacy JavaScript SDK, run `./packages/sdk/js/script/build.ts`.
 - After changing the public Protocol or Server `HttpApi`, run `bun run generate` from `packages/client`. Do not edit `src/generated` or `src/generated-effect` directly.
 - Keep runtime dependencies directed from Schema to Core and Protocol, then from Core and Protocol to Server. Client runtime code may depend on Schema and Protocol but never Core or Server; `sdk-next` composes Client, Core, and Server.
 - Do not modify `packages/opencode` unless the user explicitly asks for V1 work. `packages/opencode` is the V1 implementation and is present for reference only. New implementation changes should land in the V2 package set: `packages/core`, `packages/cli`, `packages/server`, `packages/protocol`, `packages/schema`, and related generated client surfaces when required.
@@ -60,7 +61,6 @@ const { a, b } = obj
 ### Imports
 - Never alias imports. Do not use `import { foo as bar } from "..."` or renamed imports like `resolve as pathResolve`.
 - Never use type-position `import("...")` references such as `Schema.declare<import("@opencode-ai/plugin/effect/plugin").Plugin["effect"]>`. Only when two imports genuinely collide on a name and no other option exists, an aliased type import (`import type { Plugin as PluginDefinition } from "..."`) is permitted as a last resort — still strongly preferred not to.
 - Never use star imports. Do not use `import * as Foo from "..."` or `import type * as Foo from "..."`.
 - If a namespace-style value is needed, import the module's own exported namespace by name, for example `import { Project } from "@opencode-ai/core/project"`, then reference `Project.ID`.
 - Prefer dynamic imports for heavy modules that are only needed in selected code paths, especially in startup-sensitive entrypoints. Destructure dynamic import bindings near the top of the narrowest scope that needs them so they read like normal imports. Avoid inline chains such as `await import("./module").then((mod) => mod.value())` or `(await import("./module")).value()`. Keep branch-specific imports inside the branch that needs them to preserve lazy loading.
@@ -2,7 +2,7 @@
 exact = true
 # Only install newly resolved package versions published at least 3 days ago.
 minimumReleaseAge = 259200
-minimumReleaseAgeExcludes = ["@ai-sdk/amazon-bedrock", "@ai-sdk/anthropic", "@opencode-ai/sdk", "@opentui/core", "@opentui/core-darwin-arm64", "@opentui/core-darwin-x64", "@opentui/core-linux-arm64", "@opentui/core-linux-arm64-musl", "@opentui/core-linux-x64", "@opentui/core-linux-x64-musl", "@opentui/core-win32-arm64", "@opentui/core-win32-x64", "@opentui/keymap", "@opentui/solid", "opentui-spinner", "gitlab-ai-provider", "opencode-gitlab-auth", "@ff-labs/fff-node", "@ff-labs/fff-bun", "@ff-labs/fff-bin-darwin-arm64", "@ff-labs/fff-bin-darwin-x64", "@ff-labs/fff-bin-linux-arm64-gnu", "@ff-labs/fff-bin-linux-arm64-musl", "@ff-labs/fff-bin-linux-x64-gnu", "@ff-labs/fff-bin-linux-x64-musl", "@ff-labs/fff-bin-win32-arm64", "@ff-labs/fff-bin-win32-x64", "@pierre/diffs", "@pierre/theming", "app-builder-lib", "dmg-builder", "electron-builder", "electron-publish"]
+minimumReleaseAgeExcludes = ["@ai-sdk/amazon-bedrock", "@ai-sdk/anthropic", "@opentui/core", "@opentui/core-darwin-arm64", "@opentui/core-darwin-x64", "@opentui/core-linux-arm64", "@opentui/core-linux-arm64-musl", "@opentui/core-linux-x64", "@opentui/core-linux-x64-musl", "@opentui/core-win32-arm64", "@opentui/core-win32-x64", "@opentui/keymap", "@opentui/solid", "opentui-spinner", "gitlab-ai-provider", "opencode-gitlab-auth", "@ff-labs/fff-node", "@ff-labs/fff-bun", "@ff-labs/fff-bin-darwin-arm64", "@ff-labs/fff-bin-darwin-x64", "@ff-labs/fff-bin-linux-arm64-gnu", "@ff-labs/fff-bin-linux-arm64-musl", "@ff-labs/fff-bin-linux-x64-gnu", "@ff-labs/fff-bin-linux-x64-musl", "@ff-labs/fff-bin-win32-arm64", "@ff-labs/fff-bin-win32-x64", "@pierre/diffs", "@pierre/theming", "app-builder-lib", "dmg-builder", "electron-builder", "electron-publish"]
 [test]
 root = "./do-not-run-tests-from-root"
@@ -15,6 +15,6 @@
    "@actions/github": "6.0.1",
    "@octokit/graphql": "9.0.1",
    "@octokit/rest": "catalog:",
-    "@opencode-ai/sdk": "1.18.5"
+    "@opencode-ai/sdk": "workspace:*"
  }
 }
@@ -1,8 +1,8 @@
 {
  "nodeModules": {
-    "x86_64-linux": "sha256-RFek0QoEEjsgbqmTE/SxQAmPtYyzs0IPR2ugFn5Okrs=",
+    "x86_64-linux": "sha256-qt11SKmOjq0KU542QFbs+u7YyJicn4drCcwCdg325yk=",
-    "aarch64-linux": "sha256-BmAxapY1YrAFn7mVq3/6A9+6Au5UIvSqBboHMkyJH3I=",
+    "aarch64-linux": "sha256-z68doReXTrWS7HeiAjc0btIjAsvzeZZ7hXAlHr0c77Q=",
-    "aarch64-darwin": "sha256-Sx3bGWQqLlgoa/RudJxanjSzhFRNklckT2ffnO2I5F4=",
+    "aarch64-darwin": "sha256-PILYH1Pi8XBvSkuZ+1sNnUTao5kba+m5Z8iJKx6YXPo=",
-    "x86_64-darwin": "sha256-CMOhiisHNowg06qadvgg4K+60zrynglwiT0qKYQ4NiA="
+    "x86_64-darwin": "sha256-KpcJzP4m0SUavu/WaSffgzOxrHq8ljdy0GOzs9p16lo="
  }
 }
@@ -33,12 +33,13 @@
      "packages/*",
      "packages/console/*",
      "packages/stats/*",
      "packages/sdk/js",
      "packages/slack"
    ],
    "catalog": {
-      "@effect/opentelemetry": "4.0.0-beta.101",
+      "@effect/opentelemetry": "4.0.0-beta.98",
-      "@effect/platform-node": "4.0.0-beta.101",
+      "@effect/platform-node": "4.0.0-beta.98",
-      "@effect/sql-sqlite-bun": "4.0.0-beta.101",
+      "@effect/sql-sqlite-bun": "4.0.0-beta.98",
      "@npmcli/arborist": "9.4.0",
      "@types/bun": "1.3.13",
      "@types/cross-spawn": "6.0.6",
@@ -50,7 +51,6 @@
      "@opentui/solid": "0.4.5",
      "@tanstack/solid-virtual": "3.13.32",
      "@shikijs/stream": "4.2.0",
      "@standard-schema/spec": "1.1.0",
      "ulid": "3.0.1",
      "@kobalte/core": "0.13.11",
      "@corvu/drawer": "0.2.4",
@@ -69,7 +69,7 @@
      "dompurify": "3.3.1",
      "drizzle-kit": "1.0.0-rc.2",
      "drizzle-orm": "1.0.0-rc.2",
-      "effect": "4.0.0-beta.101",
+      "effect": "4.0.0-beta.98",
      "ai": "6.0.168",
      "cross-spawn": "7.0.6",
      "hono": "4.10.7",
@@ -124,7 +124,7 @@
    "@aws-sdk/client-s3": "3.933.0",
    "@opencode-ai/plugin": "workspace:*",
    "@opencode-ai/script": "workspace:*",
-    "@opencode-ai/sdk": "1.18.5",
+    "@opencode-ai/sdk": "workspace:*",
    "heap-snapshot-toolkit": "1.1.3",
    "typescript": "catalog:"
  },
@@ -152,22 +152,21 @@
    "@opentui/keymap": "catalog:",
    "@opentui/solid": "catalog:",
    "@types/bun": "catalog:",
-    "@types/node": "catalog:",
+    "@types/node": "catalog:"
    "effect": "catalog:"
  },
  "patchedDependencies": {
    "@ff-labs/fff-bun@0.9.3": "patches/@ff-labs%2Ffff-bun@0.9.3.patch",
    "@npmcli/agent@4.0.2": "patches/@npmcli%2Fagent@4.0.2.patch",
    "@silvia-odwyer/photon-node@0.3.4": "patches/@silvia-odwyer%2Fphoton-node@0.3.4.patch",
    "@standard-community/standard-openapi@0.2.9": "patches/@standard-community%2Fstandard-openapi@0.2.9.patch",
    "solid-js@1.9.10": "patches/solid-js@1.9.10.patch",
    "@ai-sdk/xai@3.0.102": "patches/@ai-sdk%2Fxai@3.0.102.patch",
    "@ai-sdk/mistral@3.0.51": "patches/@ai-sdk%2Fmistral@3.0.51.patch",
    "gcp-metadata@8.1.2": "patches/gcp-metadata@8.1.2.patch",
    "pacote@21.5.0": "patches/pacote@21.5.0.patch",
    "@ai-sdk/google@3.0.73": "patches/@ai-sdk%2Fgoogle@3.0.73.patch",
    "@pierre/trees@1.0.0-beta.4": "patches/@pierre%2Ftrees@1.0.0-beta.4.patch",
    "@modelcontextprotocol/sdk@1.29.0": "patches/@modelcontextprotocol%2Fsdk@1.29.0.patch",
-    "effect@4.0.0-beta.101": "patches/effect@4.0.0-beta.101.patch",
+    "effect@4.0.0-beta.98": "patches/effect@4.0.0-beta.98.patch",
    "@tanstack/virtual-core@3.17.3": "patches/@tanstack%2Fvirtual-core@3.17.3.patch"
  }
 }
@@ -54,7 +54,7 @@ Filter or narrow `LLMEvent` streams with `LLMEvent.is.*` (camelCase guards, e.g.
 A route is the registered, runnable composition of four orthogonal pieces:
- **`Protocol`** (`src/route/protocol.ts`) — semantic API contract. Owns request body construction (`body.from`), the body schema (`body.schema`), the streaming-event schema (`stream.event`), and the event-to-`LLMEvent` state machine (`stream.step`). `Route.make(...)` validates and JSON-encodes the body from `body.schema` and decodes frames with `stream.event`. Examples: `OpenAIChat.protocol`, `OpenResponses.protocol`, `OpenAIResponses.protocol`, `AnthropicMessages.protocol`, `Gemini.protocol`, `BedrockConverse.protocol`.
+- **`Protocol`** (`src/route/protocol.ts`) — semantic API contract. Owns request body construction (`body.from`), the body schema (`body.schema`), the streaming-event schema (`stream.event`), and the event-to-`LLMEvent` state machine (`stream.step`). `Route.make(...)` validates and JSON-encodes the body from `body.schema` and decodes frames with `stream.event`. Examples: `OpenAIChat.protocol`, `OpenAIResponses.protocol`, `AnthropicMessages.protocol`, `Gemini.protocol`, `BedrockConverse.protocol`.
 - **`Endpoint`** (`src/route/endpoint.ts`) — URL construction. The host, path, and route query live on the endpoint. `Endpoint.path("/chat/completions", { baseURL })` is the common case; pass a function for paths that embed the model id or a body field (e.g. `Endpoint.path(({ body }) => `/model/${body.modelId}/converse-stream`)`).
 - **`Auth`** (`src/route/auth.ts`) — per-request transport authentication. Provider facades configure credentials onto the route before model selection, usually via `Auth.bearer(apiKey)` or `Auth.header(name, apiKey)`. Routes that need per-request signing (Bedrock SigV4, future Vertex IAM, Azure AAD) implement `Auth` as a function that signs the body and merges signed headers into the result.
 - **`Framing`** (`src/route/framing.ts`) — bytes → frames. SSE (`Framing.sse`) is shared; Bedrock keeps its AWS event-stream framing as a typed `Framing<object>` value alongside its protocol.
@@ -158,14 +158,13 @@ packages/ai/src/
  protocols/
    shared.ts               ProviderShared toolkit used inside protocol impls
    openai-chat.ts          protocol + route (compose OpenAIChat.protocol)
-    open-responses.ts         provider-neutral Responses protocol baseline
+    openai-responses.ts
    openai-responses.ts       OpenAI tools/events/transports composed over OpenResponses
    anthropic-messages.ts
    gemini.ts
    bedrock-converse.ts
    bedrock-event-stream.ts framing for AWS event-stream binary frames
    openai-compatible-chat.ts route that reuses OpenAIChat.protocol, no canonical URL
-    openai-compatible-responses.ts deployment adapter that reuses OpenResponses.protocol, no canonical URL
+    openai-compatible-responses.ts route that reuses OpenAIResponses.protocol, no canonical URL
    utils/                  per-protocol helpers (auth, cache, media, tool-stream, ...)
  providers/
    openai-compatible.ts    generic Chat helper + family model helpers
@@ -176,7 +175,7 @@ packages/ai/src/
  tool-runtime.ts           narrow one-call typed tool dispatcher
 ```
-The dependency arrow points down: `providers/*.ts` files import protocol routes and auth-option utilities; protocol modules import `endpoint`, `auth`, `framing`, and transport pieces. Protocols do not import provider facades. Lower-level modules know nothing about provider catalog metadata. `OpenAIResponses` composes the provider-neutral `OpenResponses` protocol; the baseline never imports the OpenAI extension.
+The dependency arrow points down: `providers/*.ts` files import protocol routes and auth-option utilities; protocol modules import `endpoint`, `auth`, `framing`, and transport pieces. Protocols do not import provider facades. Lower-level modules know nothing about provider catalog metadata.
 ### Shared protocol helpers
@@ -241,7 +240,7 @@ const get_weather = tool({
 const tools = { get_weather, get_time, ... }
 const events = yield* LLM.stream(
-  LLMRequest.update(request, { tools: Tool.toDefinitions(tools) }),
+  LLM.updateRequest(request, { tools: Tool.toDefinitions(tools) }),
 ).pipe(Stream.runCollect)
 const call = Array.from(events).find(LLMEvent.is.toolCall)
@@ -315,8 +315,7 @@ const longer = {
 }
 ```
-There is no `LLM.updateRequest(...)` helper. The current Schema-backed implementation
+There is no `LLM.updateRequest(...)` helper and no request Schema class.
 uses `LLMRequest.update(...)` when canonical request data must be derived.
 ### Conversation history
@@ -437,7 +436,7 @@ const call = Array.from(events).find(LLMEvent.is.toolCall)
 if (call && !call.providerExecuted) {
  const dispatched = yield * ToolRuntime.dispatch(tools, call)
-  const followUp = LLMRequest.update(request, {
+  const followUp = LLM.updateRequest(request, {
    messages: [...request.messages, Message.assistant([call]), Message.tool({ ...call, result: dispatched.result })],
  })
  // Caller must invoke the provider again and repeat the loop.
@@ -207,9 +207,7 @@ Prompt caching is **on by default**. Every `LLMRequest` resolves to `cache: "aut
 ### Auto placement
-`"auto"` places up to four breakpoints — the last tool definition, the first system part, the last system part when distinct, and the final message boundary. These expose successively larger reusable prefixes for tools, the base agent, project instructions, and the active conversation. The rolling final-message boundary is the load-bearing detail in tool loops: it advances on every request so the previous cache entry stays within Anthropic's 20-block lookback.
+`"auto"` places three breakpoints — last tool definition, last system part, latest user message. The last-user-message boundary is the load-bearing detail: in a tool-use loop, a single user turn expands into many assistant/tool round-trips, all sharing that prefix. Caching at that boundary lets every intra-turn API call hit.
 Tools precede every system and conversation block in the provider prefix, so tool definitions must remain byte-stable and deterministically ordered for downstream breakpoints to remain reusable.
 The math justifies the default: Anthropic's 5-minute cache write is 1.25× base, read is 0.1×, so a single reuse within 5 minutes already wins. One-shot completions below the per-model minimum-cacheable-token threshold silently no-op on the wire, so the worst case is harmless.
@@ -237,7 +235,7 @@ cache: {
 ### Manual hints
-Inline `CacheHint` on any text / system / tool / tool-result part overrides automatic placement. The auto policy preserves manual hints, counts them against Anthropic and Bedrock's four-breakpoint limit, and only fills the remaining slots.
+Inline `CacheHint` on any text / system / tool / tool-result part overrides automatic placement. The auto policy preserves manual hints; it only fills gaps.
 ```ts
 LLM.request({
@@ -253,8 +251,8 @@ LLM.request({
 | Protocol                | `cache: "auto"`                                                           |
 | ----------------------- | ------------------------------------------------------------------------- |
-| Anthropic Messages      | emits up to 4 `cache_control` markers (4-breakpoint cap enforced)         |
+| Anthropic Messages      | emits up to 3 `cache_control` markers (4-breakpoint cap enforced)         |
-| Bedrock Converse        | emits up to 4 `cachePoint` blocks (4-breakpoint cap enforced)             |
+| Bedrock Converse        | emits up to 3 `cachePoint` blocks (4-breakpoint cap enforced)             |
 | OpenAI Chat / Responses | no-op (implicit caching above 1024 tokens)                                |
 | Gemini                  | no-op (implicit caching on 2.5+; explicit `CachedContent` is out-of-band) |
@@ -302,7 +300,7 @@ OpenAI Chat and OpenAI Responses are separate semantic entrypoints:
 - `@opencode-ai/ai/providers/google-vertex/responses`
 - `@opencode-ai/ai/providers/google-vertex/messages`
-Responses HTTP versus WebSocket is a scoped `transport` setting on the OpenAI Responses entrypoint, not another entrypoint. Azure follows the same Chat/Responses split at `providers/azure/chat` and `providers/azure/responses`. Generic OpenAI-compatible Chat remains at `providers/openai-compatible`; the Responses adapter at `providers/openai-compatible/responses` uses the provider-neutral Open Responses protocol. OpenAI Responses extends that baseline with OpenAI tools, event variants, metadata, defaults, and transports. Generic Anthropic Messages-compatible providers use `providers/anthropic-compatible`, which the named Anthropic provider composes. Google Gemini and Amazon Bedrock expose their single native API through their existing provider paths.
+Responses HTTP versus WebSocket is a scoped `transport` setting on the OpenAI Responses entrypoint, not another entrypoint. Azure follows the same Chat/Responses split at `providers/azure/chat` and `providers/azure/responses`. Generic OpenAI-compatible Chat remains at `providers/openai-compatible`; compatible Responses is separate at `providers/openai-compatible/responses`. Generic Anthropic Messages-compatible providers use `providers/anthropic-compatible`, which the named Anthropic provider composes. Google Gemini and Amazon Bedrock expose their single native API through their existing provider paths.
 Vertex Gemini, Vertex Chat, Vertex Responses, and Vertex Messages are separate API entrypoints. All accept `project`, `location`, and an optional `accessToken`; when no explicit token or auth override is supplied they lazily use Google Application Default Credentials. Vertex Gemini instead selects express mode when `apiKey` or `GOOGLE_VERTEX_API_KEY` is present. Vertex Chat targets MaaS models through the OpenAI-compatible Chat Completions endpoint, while Vertex Responses targets Grok models and defaults `store` to `false` as required by Vertex. `providers/google-vertex` remains the default alias for `providers/google-vertex/gemini`.
@@ -1,6 +1,6 @@
 # LLM Provider Parity Status
-Last reviewed: 2026-07-24
+Last reviewed: 2026-07-17
 This file tracks the gap between the native `@opencode-ai/ai` package and the AI SDK provider packages that opencode still depends on for many catalog/runtime paths.
@@ -13,26 +13,26 @@ This file tracks the gap between the native `@opencode-ai/ai` package and the AI
 ## Current Implementation Snapshot
-| Native slice                       | Source                                                                                                                            | Current state                                                                                                                                                            | Main gaps                                                                                                                                                                                                                                                 |
+| Native slice                       | Source                                                                                         | Current state                                                                                                                                                            | Main gaps                                                                                                                                                                                                                                                 |
-| ---------------------------------- | --------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| ---------------------------------- | ---------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| OpenAI Chat                        | `src/protocols/openai-chat.ts`, `src/providers/openai.ts`                                                                         | Usable. Streams text, reasoning deltas, tool calls, usage, images, and common generation controls.                                                                       | No typed structured-output / `response_format` path. Limited typed OpenAI option surface compared with SDK escape hatches.                                                                                                                                |
+| OpenAI Chat                        | `src/protocols/openai-chat.ts`, `src/providers/openai.ts`                                      | Usable. Streams text, reasoning deltas, tool calls, usage, images, and common generation controls.                                                                       | No typed structured-output / `response_format` path. Limited typed OpenAI option surface compared with SDK escape hatches.                                                                                                                                |
-| OpenAI Responses HTTP              | `src/protocols/open-responses.ts`, `src/protocols/openai-responses.ts`, `src/providers/openai.ts`                                 | Usable. Extends the Open Responses baseline with hosted-tool event surfacing, reasoning replay metadata, GPT-5 defaults, and cache usage.                                | No explicit `previous_response_id` path. Typed options cover only a subset of Responses fields. Structured output is still mostly synthetic-tool based.                                                                                                   |
+| OpenAI Responses HTTP              | `src/protocols/openai-responses.ts`, `src/providers/openai.ts`                                 | Usable. Supports hosted-tool event surfacing, reasoning replay metadata, GPT-5 defaults, and cache usage.                                                                | No explicit `previous_response_id` path. Typed options cover only a subset of Responses fields. Structured output is still mostly synthetic-tool based.                                                                                                   |
-| OpenAI Responses WebSocket         | `src/protocols/openai-responses.ts`, `src/route/transport/websocket.ts`                                                           | Present as `OpenAI.responsesWebSocket(...)`.                                                                                                                             | Runner/catalog support explicitly must not downgrade WebSocket routes; broader runtime selection is not complete.                                                                                                                                         |
+| OpenAI Responses WebSocket         | `src/protocols/openai-responses.ts`, `src/route/transport/websocket.ts`                        | Present as `OpenAI.responsesWebSocket(...)`.                                                                                                                             | Runner/catalog support explicitly must not downgrade WebSocket routes; broader runtime selection is not complete.                                                                                                                                         |
-| OpenAI-compatible Chat             | `src/protocols/openai-compatible-chat.ts`, `src/providers/openai-compatible.ts`                                                   | Usable for generic Chat and several profiles: Baseten, Cerebras, DeepInfra, DeepSeek, Fireworks, Groq, TogetherAI.                                                       | Family quirks are mostly endpoint defaults, not full typed behavior.                                                                                                                                                                                      |
+| OpenAI-compatible Chat             | `src/protocols/openai-compatible-chat.ts`, `src/providers/openai-compatible.ts`                | Usable for generic Chat and several profiles: Baseten, Cerebras, DeepInfra, DeepSeek, Fireworks, Groq, TogetherAI.                                                       | Family quirks are mostly endpoint defaults, not full typed behavior.                                                                                                                                                                                      |
-| Open Responses-compatible          | `src/protocols/open-responses.ts`, `src/protocols/openai-compatible-responses.ts`, `src/providers/openai-compatible-responses.ts` | Usable for deployments that implement the provider-neutral Open Responses protocol. The deployment adapter does not inherit OpenAI tools, events, metadata, or defaults. | No named family profiles or recorded deployment coverage yet.                                                                                                                                                                                             |
+| OpenAI-compatible Responses        | `src/protocols/openai-compatible-responses.ts`, `src/providers/openai-compatible-responses.ts` | Usable for deployments that implement the OpenAI Responses wire protocol.                                                                                                | No named family profiles or recorded deployment coverage yet.                                                                                                                                                                                             |
-| Anthropic-compatible Messages      | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic-compatible.ts`                                                    | Usable for deployments that implement the Anthropic Messages wire protocol. Named Anthropic composes this base; MiniMax M3 has recorded text and tool-loop coverage.     | No named compatible family profiles yet.                                                                                                                                                                                                                  |
+| Anthropic-compatible Messages      | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic-compatible.ts`                 | Usable for deployments that implement the Anthropic Messages wire protocol. Named Anthropic composes this base; MiniMax M3 has recorded text and tool-loop coverage.       | No named compatible family profiles yet.                                                                                                                                                                                                                  |
-| Anthropic Messages                 | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic.ts`                                                               | Usable. Supports tools, thinking, cache control, images, server-hosted tool events, and usage.                                                                           | Provider option surface is small. Beta/header handling, metadata, and newer Messages fields need a typed parity pass.                                                                                                                                     |
+| Anthropic Messages                 | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic.ts`                            | Usable. Supports tools, thinking, cache control, images, server-hosted tool events, and usage.                                                                           | Provider option surface is small. Beta/header handling, metadata, and newer Messages fields need a typed parity pass.                                                                                                                                     |
-| Gemini Developer API               | `src/protocols/gemini.ts`, `src/providers/google.ts`                                                                              | Usable for Google API key flow. Supports text, images, tools, thinking signatures, and cache usage.                                                                      | This is not Vertex. Typed provider options are narrow; many Gemini request fields currently require raw `http.body` overlays.                                                                                                                             |
+| Gemini Developer API               | `src/protocols/gemini.ts`, `src/providers/google.ts`                                           | Usable for Google API key flow. Supports text, images, tools, thinking signatures, and cache usage.                                                                      | This is not Vertex. Typed provider options are narrow; many Gemini request fields currently require raw `http.body` overlays.                                                                                                                             |
-| Vertex Gemini                      | `src/protocols/gemini.ts`, `src/providers/google-vertex.ts`                                                                       | Usable through API-key express mode, explicit OAuth tokens, or ADC with project/location endpoint derivation, including tuned `endpoints/...` deployments.               | Core runner/catalog mapping and recorded provider coverage are missing.                                                                                                                                                                                   |
+| Vertex Gemini                      | `src/protocols/gemini.ts`, `src/providers/google-vertex.ts`                                    | Usable through API-key express mode, explicit OAuth tokens, or ADC with project/location endpoint derivation, including tuned `endpoints/...` deployments.               | Core runner/catalog mapping and recorded provider coverage are missing.                                                                                                                                                                                   |
-| Vertex Chat                        | `src/protocols/openai-chat.ts`, `src/providers/google-vertex-chat.ts`                                                             | Usable for MaaS models through OpenAI-compatible Chat Completions with explicit OAuth tokens or ADC and project/location endpoint derivation.                            | Core runner/catalog mapping and recorded provider coverage are missing; MaaS family-specific request parity needs review.                                                                                                                                 |
+| Vertex Chat                        | `src/protocols/openai-chat.ts`, `src/providers/google-vertex-chat.ts`                          | Usable for MaaS models through OpenAI-compatible Chat Completions with explicit OAuth tokens or ADC and project/location endpoint derivation.                            | Core runner/catalog mapping and recorded provider coverage are missing; MaaS family-specific request parity needs review.                                                                                                                                 |
-| Vertex Responses                   | `src/protocols/open-responses.ts`, `src/providers/google-vertex-responses.ts`                                                     | Usable for Grok models through Open Responses with explicit OAuth tokens or ADC, project/location endpoint derivation, and an explicit `store: false` Vertex default.    | Core runner/catalog mapping and recorded provider coverage are missing; stateful continuation is not supported by Vertex.                                                                                                                                 |
+| Vertex Responses                   | `src/protocols/openai-responses.ts`, `src/providers/google-vertex-responses.ts`                | Usable for Grok models through OpenAI-compatible Responses with explicit OAuth tokens or ADC, project/location endpoint derivation, and storage disabled by default.     | Core runner/catalog mapping and recorded provider coverage are missing; stateful continuation is not supported by Vertex.                                                                                                                                 |
-| Vertex Messages                    | `src/protocols/anthropic-messages.ts`, `src/providers/google-vertex-messages.ts`                                                  | Usable through explicit OAuth tokens or ADC, including global, regional, and `eu`/`us` multi-region endpoints.                                                           | Core runner/catalog mapping and recorded provider coverage are missing; Vertex-specific hosted-tool parity needs review.                                                                                                                                  |
+| Vertex Messages                    | `src/protocols/anthropic-messages.ts`, `src/providers/google-vertex-messages.ts`               | Usable through explicit OAuth tokens or ADC, including global, regional, and `eu`/`us` multi-region endpoints.                                                           | Core runner/catalog mapping and recorded provider coverage are missing; Vertex-specific hosted-tool parity needs review.                                                                                                                                  |
-| Bedrock Converse                   | `src/protocols/bedrock-converse.ts`, `src/providers/amazon-bedrock.ts`                                                            | Partial but real. Supports AWS event-stream framing, SigV4 with supplied credentials, bearer auth, tools, reasoning signatures, media, cache points, and recorded tests. | Native facade does not mirror the AI SDK plugin's default AWS credential chain/profile behavior. Runner/catalog mapping is missing. Guardrails, inference profiles, region-specific model ID fixes, and model-specific request fields need a parity pass. |
+| Bedrock Converse                   | `src/protocols/bedrock-converse.ts`, `src/providers/amazon-bedrock.ts`                         | Partial but real. Supports AWS event-stream framing, SigV4 with supplied credentials, bearer auth, tools, reasoning signatures, media, cache points, and recorded tests. | Native facade does not mirror the AI SDK plugin's default AWS credential chain/profile behavior. Runner/catalog mapping is missing. Guardrails, inference profiles, region-specific model ID fixes, and model-specific request fields need a parity pass. |
-| Azure OpenAI                       | `src/providers/azure.ts` using OpenAI Chat/Responses protocols                                                                    | Partial. Supports resource/base URL setup, API key auth, API version query, Chat, and Responses selectors.                                                               | Core runner does not map `@ai-sdk/azure` to this native facade. AAD/token auth and Azure-specific endpoint variants need review.                                                                                                                          |
+| Azure OpenAI                       | `src/providers/azure.ts` using OpenAI Chat/Responses protocols                                 | Partial. Supports resource/base URL setup, API key auth, API version query, Chat, and Responses selectors.                                                               | Core runner does not map `@ai-sdk/azure` to this native facade. AAD/token auth and Azure-specific endpoint variants need review.                                                                                                                          |
-| Cloudflare AI Gateway / Workers AI | `src/providers/cloudflare.ts`                                                                                                     | Present via OpenAI-compatible Chat routes.                                                                                                                               | Useful but not part of the critical AI SDK replacement set yet. Needs per-product recorded coverage before relying on it broadly.                                                                                                                         |
+| Cloudflare AI Gateway / Workers AI | `src/providers/cloudflare.ts`                                                                  | Present via OpenAI-compatible Chat routes.                                                                                                                               | Useful but not part of the critical AI SDK replacement set yet. Needs per-product recorded coverage before relying on it broadly.                                                                                                                         |
-| OpenRouter                         | `src/providers/openrouter.ts`                                                                                                     | Present with OpenRouter-specific usage/reasoning/prompt-cache options over Chat.                                                                                         | Responses-style OpenRouter support is absent.                                                                                                                                                                                                             |
+| OpenRouter                         | `src/providers/openrouter.ts`                                                                  | Present with OpenRouter-specific usage/reasoning/prompt-cache options over Chat.                                                                                         | Responses-style OpenRouter support is absent.                                                                                                                                                                                                             |
-| xAI                                | `src/providers/xai.ts`                                                                                                            | Present with Responses and Chat selectors.                                                                                                                               | Needs package-parity review against the AI SDK xAI provider.                                                                                                                                                                                              |
+| xAI                                | `src/providers/xai.ts`                                                                         | Present with Responses and Chat selectors.                                                                                                                               | Needs package-parity review against the AI SDK xAI provider.                                                                                                                                                                                              |
-| GitHub Copilot                     | `src/providers/github-copilot.ts`                                                                                                 | Present as explicit-base-URL OpenAI Chat/Responses facade.                                                                                                               | Runtime/catalog integration remains specialized and should stay separate from public OpenAI-compatible defaults.                                                                                                                                          |
+| GitHub Copilot                     | `src/providers/github-copilot.ts`                                                              | Present as explicit-base-URL OpenAI Chat/Responses facade.                                                                                                               | Runtime/catalog integration remains specialized and should stay separate from public OpenAI-compatible defaults.                                                                                                                                          |
 ## V2 Runner Status
@@ -65,7 +65,7 @@ Other `aisdk:` packages, including Google Vertex, Azure, and Bedrock, currently
 ## Highest-Risk Gaps
 1. Runner support is narrower than the LLM package. The package has native provider facades for Google, Azure, and Bedrock, but the V2 Session runner only maps OpenAI, Anthropic, and explicit OpenAI-compatible Chat from `aisdk` catalog metadata.
-2. The Open Responses adapter is available through a separate package entrypoint, but the V2 runner still maps `@ai-sdk/openai-compatible` to Chat only. Catalog selection must become API-aware before Responses deployments can use it.
+2. OpenAI-compatible Responses is available as a separate package entrypoint, but the V2 runner still maps `@ai-sdk/openai-compatible` to Chat only. Catalog selection must become API-aware before Responses deployments can use it.
 3. Bedrock native auth is not AI SDK parity. The AI SDK plugin uses the default AWS provider chain, profile, container credentials, and Bedrock bearer token env behavior. Native Bedrock currently expects explicit credentials or bearer auth on the facade.
 4. Vertex Gemini, Vertex Chat, Vertex Responses, and Vertex Messages now have native package entrypoints, but the core runner does not map catalog metadata to them yet and recorded provider coverage is still missing.
 5. Azure is only a provider facade, not a full runtime replacement. Native Azure exists, but the catalog runner does not select it, and token auth/resource variants need review.
@@ -83,13 +83,13 @@ These are implementation/API slices, not separate npm packages.
 | OpenAI Chat                   | `@opencode-ai/ai/providers/openai/chat`                 | OpenAI `/chat/completions` semantics.                                        |
 | OpenAI Responses              | `@opencode-ai/ai/providers/openai/responses`            | OpenAI `/responses` semantics with HTTP/WebSocket selected through settings. |
 | OpenAI-compatible Chat        | `@opencode-ai/ai/providers/openai-compatible`           | Generic OpenAI-compatible `/chat/completions`.                               |
-| Open Responses-compatible     | `@opencode-ai/ai/providers/openai-compatible/responses` | Generic provider-neutral `/responses`.                                       |
+| OpenAI-compatible Responses   | `@opencode-ai/ai/providers/openai-compatible/responses` | Generic OpenAI-compatible `/responses`.                                      |
 | Anthropic-compatible Messages | `@opencode-ai/ai/providers/anthropic-compatible`        | Generic Anthropic-compatible `/messages`.                                    |
 | Anthropic Messages            | `@opencode-ai/ai/providers/anthropic`                   | Anthropic Messages API.                                                      |
 | Gemini Developer API          | `@opencode-ai/ai/providers/google`                      | Google AI Studio Gemini API.                                                 |
 | Vertex Gemini                 | `@opencode-ai/ai/providers/google-vertex/gemini`        | Vertex Gemini API; `providers/google-vertex` is the default alias.           |
 | Vertex Chat                   | `@opencode-ai/ai/providers/google-vertex/chat`          | Vertex OpenAI-compatible Chat Completions for MaaS models.                   |
-| Vertex Responses              | `@opencode-ai/ai/providers/google-vertex/responses`     | Vertex Open Responses for Grok models.                                       |
+| Vertex Responses              | `@opencode-ai/ai/providers/google-vertex/responses`     | Vertex OpenAI-compatible Responses for Grok models.                          |
 | Vertex Messages               | `@opencode-ai/ai/providers/google-vertex/messages`      | Vertex-hosted Anthropic Messages API.                                        |
 | Bedrock Converse              | `@opencode-ai/ai/providers/amazon-bedrock`              | AWS Bedrock Converse API.                                                    |
 | Bedrock Mantle                | Missing                                                 | AWS Bedrock Mantle OpenAI-compatible APIs.                                   |
@@ -1,5 +1,5 @@
 import { Config, Effect, Formatter, Layer, Schema, Stream } from "effect"
-import { LLM, LLMClient, LLMRequest, Message, ProviderID, Tool, ToolRuntime } from "@opencode-ai/ai"
+import { LLM, LLMClient, Message, ProviderID, Tool, ToolRuntime } from "@opencode-ai/ai"
 import { Route, Auth, Endpoint, Framing, Protocol, RequestExecutor, WebSocketExecutor } from "@opencode-ai/ai/route"
 import { OpenAI } from "@opencode-ai/ai/providers"
@@ -78,10 +78,7 @@ const streamText = LLM.stream(request).pipe(
  Stream.tap((event) =>
    Effect.sync(() => {
      if (event.type === "text-delta") process.stdout.write(`\ntext: ${event.text}`)
-      if (event.type === "finish")
+      if (event.type === "finish") process.stdout.write(`\nfinish: ${event.reason}\n`)
        process.stdout.write(
          `\nfinish: ${event.reason.normalized}${event.reason.raw ? ` (${event.reason.raw})` : ""}\n`,
        )
    }),
  ),
  Stream.runDrain,
@@ -116,7 +113,7 @@ const streamWithTools = Effect.gen(function* () {
    // A durable agent would persist these messages before starting another
    // raw model turn. This tutorial keeps the boundary visible instead.
-    const followUp = LLMRequest.update(request, {
+    const followUp = LLM.updateRequest(request, {
      messages: [
        ...request.messages,
        Message.assistant([event]),
@@ -197,7 +194,7 @@ const FakeProtocol = Protocol.make<FakeBody, string, string, void>({
    event: Schema.String,
    initial: () => undefined,
    step: (_, frame) => Effect.succeed([undefined, [{ type: "text-delta", id: "text-0", text: frame }]] as const),
-    onHalt: () => [{ type: "finish", reason: { normalized: "stop" } }],
+    onHalt: () => [{ type: "finish", reason: "stop" }],
  },
 })
@@ -15,7 +15,6 @@
  ],
  "exports": {
    ".": "./src/index.ts",
    "./testing": "./src/testing.ts",
    "./*": "./src/*.ts"
  },
  "devDependencies": {
@@ -2,31 +2,32 @@
 // the policy designates. Runs once at compile time, before the per-protocol
 // body builder, so the existing inline-hint lowering path handles the rest.
 //
-// The default `"auto"` shape places breakpoints at the last tool definition,
+// The default `"auto"` shape places one breakpoint at the last tool definition,
-// the first and last distinct system parts, and the conversation tail. This
+// one at the last system part, and one at the latest user message. This
-// exposes reusable tool, base-agent, project, and session prefixes while
+// matches what production agent harnesses (LangChain's caching middleware,
-// advancing the tail after each tool result keeps the previous cache entry
+// kern-ai's 10x cost-reduction playbook) converge on for tool-use loops: the
-// within Anthropic's 20-block lookback during long agent turns.
+// latest user message stays put while a single turn explodes into many
 // assistant/tool round-trips, so caching at that boundary lets every
 // intra-turn API call hit the prefix.
 //
-// Manual `cache: CacheHint` placements on individual parts are preserved and
+// Manual `cache: CacheHint` placements on individual parts are preserved —
-// count against the four-breakpoint budget; auto only fills remaining slots.
+// this function only fills gaps the caller left empty.
 import { CacheHint, type CachePolicy, type CachePolicyObject } from "./schema/options"
 import { LLMRequest, Message, ToolDefinition, type ContentPart } from "./schema/messages"
 const AUTO: CachePolicyObject = {
  tools: true,
  system: true,
-  messages: { tail: 1 },
+  messages: "latest-user-message",
 }
 const NONE: CachePolicyObject = {}
 const BREAKPOINT_CAP = 4
 // Resolution rules:
 //   - undefined   → "auto" — caching is on by default. The math favors it:
 //                   Anthropic 5m-cache write is 1.25x base, read is 0.1x,
 //                   so a single reuse within 5 minutes already wins.
-//   - "auto"      → tools + first/last system + final message boundary.
+//   - "auto"      → tools + system + latest user msg.
 //   - "none"      → no auto placement; manual `CacheHint`s still flow.
 //   - object form → exactly what the caller asked for.
 const resolve = (policy: CachePolicy | undefined): CachePolicyObject => {
@@ -43,32 +44,18 @@ const RESPECTS_INLINE_HINTS = new Set(["anthropic-messages", "bedrock-converse"]
 const makeHint = (ttlSeconds: number | undefined): CacheHint =>
  ttlSeconds !== undefined ? new CacheHint({ type: "ephemeral", ttlSeconds }) : new CacheHint({ type: "ephemeral" })
-interface Budget {
+const markLastTool = (tools: ReadonlyArray<ToolDefinition>, hint: CacheHint): ReadonlyArray<ToolDefinition> => {
  remaining: number
 }
 const markLastTool = (
  tools: ReadonlyArray<ToolDefinition>,
  hint: CacheHint,
  budget: Budget,
 ): ReadonlyArray<ToolDefinition> => {
  if (tools.length === 0) return tools
  const last = tools.length - 1
-  if (tools[last]!.cache || budget.remaining === 0) return tools
+  if (tools[last]!.cache) return tools
  budget.remaining -= 1
  return tools.map((tool, i) => (i === last ? new ToolDefinition({ ...tool, cache: hint }) : tool))
 }
-const markSystemBoundaries = (system: LLMRequest["system"], hint: CacheHint, budget: Budget): LLMRequest["system"] => {
+const markLastSystem = (system: LLMRequest["system"], hint: CacheHint): LLMRequest["system"] => {
  if (system.length === 0) return system
-  let changed = false
+  const last = system.length - 1
-  const next = system.map((part, index) => {
+  if (system[last]!.cache) return system
-    if ((index !== 0 && index !== system.length - 1) || part.cache || budget.remaining === 0) return part
+  return system.map((part, i) => (i === last ? { ...part, cache: hint } : part))
    budget.remaining -= 1
    changed = true
    return { ...part, cache: hint }
  })
  return changed ? next : system
 }
 const lastIndexOfRole = (messages: ReadonlyArray<Message>, role: Message["role"]): number =>
@@ -77,20 +64,14 @@ const lastIndexOfRole = (messages: ReadonlyArray<Message>, role: Message["role"]
 // Mark the last text part of `messages[index]`. If no text part exists, mark
 // the last content part regardless of type — that's the breakpoint position
 // in tool-result-only messages too.
-const markMessageAt = (
+const markMessageAt = (messages: ReadonlyArray<Message>, index: number, hint: CacheHint): ReadonlyArray<Message> => {
  messages: ReadonlyArray<Message>,
  index: number,
  hint: CacheHint,
  budget: Budget,
 ): ReadonlyArray<Message> => {
  if (index < 0 || index >= messages.length) return messages
  const target = messages[index]!
  if (target.content.length === 0) return messages
  const lastTextIndex = target.content.findLastIndex((part) => part.type === "text")
  const markAt = lastTextIndex >= 0 ? lastTextIndex : target.content.length - 1
  const existing = target.content[markAt]!
-  if (("cache" in existing && existing.cache) || budget.remaining === 0) return messages
+  if ("cache" in existing && existing.cache) return messages
  budget.remaining -= 1
  const nextContent = target.content.map((part, i) => (i === markAt ? ({ ...part, cache: hint } as ContentPart) : part))
  const next = new Message({ ...target, content: nextContent })
  // Single pass over `messages`, substituting the one updated entry. Long
@@ -105,42 +86,25 @@ const markMessages = (
  messages: ReadonlyArray<Message>,
  strategy: NonNullable<CachePolicyObject["messages"]>,
  hint: CacheHint,
  budget: Budget,
 ): ReadonlyArray<Message> => {
  if (messages.length === 0) return messages
-  if (strategy === "latest-user-message")
+  if (strategy === "latest-user-message") return markMessageAt(messages, lastIndexOfRole(messages, "user"), hint)
-    return markMessageAt(messages, lastIndexOfRole(messages, "user"), hint, budget)
+  if (strategy === "latest-assistant") return markMessageAt(messages, lastIndexOfRole(messages, "assistant"), hint)
  if (strategy === "latest-assistant")
    return markMessageAt(messages, lastIndexOfRole(messages, "assistant"), hint, budget)
  const start = Math.max(0, messages.length - strategy.tail)
  let next = messages
-  for (let i = start; i < messages.length; i++) next = markMessageAt(next, i, hint, budget)
+  for (let i = start; i < messages.length; i++) next = markMessageAt(next, i, hint)
  return next
 }
 const countHints = (request: LLMRequest) =>
  request.tools.reduce((count, tool) => count + (tool.cache === undefined ? 0 : 1), 0) +
  request.system.reduce((count, part) => count + (part.cache === undefined ? 0 : 1), 0) +
  request.messages.reduce(
    (count, message) =>
      count +
      message.content.reduce(
        (contentCount, part) => contentCount + ("cache" in part && part.cache !== undefined ? 1 : 0),
        0,
      ),
    0,
  )
 export const applyCachePolicy = (request: LLMRequest): LLMRequest => {
  if (!RESPECTS_INLINE_HINTS.has(request.model.route.id)) return request
  const policy = resolve(request.cache)
  if (!policy.tools && !policy.system && !policy.messages) return request
  const hint = makeHint(policy.ttlSeconds)
-  const budget = { remaining: Math.max(0, BREAKPOINT_CAP - countHints(request)) }
+  const tools = policy.tools ? markLastTool(request.tools, hint) : request.tools
-  const tools = policy.tools ? markLastTool(request.tools, hint, budget) : request.tools
+  const system = policy.system ? markLastSystem(request.system, hint) : request.system
-  const system = policy.system ? markSystemBoundaries(request.system, hint, budget) : request.system
+  const messages = policy.messages ? markMessages(request.messages, policy.messages, hint) : request.messages
  const messages = policy.messages ? markMessages(request.messages, policy.messages, hint, budget) : request.messages
  if (tools === request.tools && system === request.system && messages === request.messages) return request
  return LLMRequest.update(request, { tools, system, messages })
@@ -9,13 +9,24 @@ import {
  LLMRequest,
  LLMResponse,
  Message,
  type ModelInput as SchemaModelInput,
  SystemPart,
  ToolChoice,
  ToolDefinition,
  type ContentPart,
  ToolResultPart,
 } from "./schema"
 import { make as makeTool, toDefinitions, type ToolSchema } from "./tool"
 export type ModelInput = SchemaModelInput
 export type MessageInput = Message.Input
 export type ToolChoiceInput = ToolChoice.Input
 export type ToolChoiceMode = ToolChoice.Mode
 export type ToolResultInput = Parameters<typeof ToolResultPart.make>[0]
 /** Input accepted by `LLM.request`, normalized into the canonical `LLMRequest` class. */
 export type RequestInput = Omit<
  ConstructorParameters<typeof LLMRequest>[0],
@@ -23,9 +34,9 @@ export type RequestInput = Omit<
 > & {
  readonly system?: string | SystemPart | ReadonlyArray<SystemPart>
  readonly prompt?: string | ContentPart | ReadonlyArray<ContentPart>
-  readonly messages?: ReadonlyArray<Message | Message.Input>
+  readonly messages?: ReadonlyArray<Message | MessageInput>
  readonly tools?: ReadonlyArray<ToolDefinition.Input>
-  readonly toolChoice?: ToolChoice.Input
+  readonly toolChoice?: ToolChoiceInput
  readonly generation?: GenerationOptions.Input
  readonly providerOptions?: ConstructorParameters<typeof LLMRequest>[0]["providerOptions"]
  readonly http?: HttpOptions.Input
@@ -35,6 +46,10 @@ export const generate = LLMClient.generate
 export const stream = LLMClient.stream
 export const requestInput = (input: LLMRequest): RequestInput => ({
  ...LLMRequest.input(input),
 })
 export const request = (input: RequestInput) => {
  const {
    system: requestSystem,
@@ -59,11 +74,14 @@ export const request = (input: RequestInput) => {
  })
 }
 export const updateRequest = (input: LLMRequest, patch: Partial<RequestInput>) =>
  request({ ...requestInput(input), ...patch })
 const GENERATE_OBJECT_TOOL_NAME = "generate_object"
 const GENERATE_OBJECT_TOOL_DESCRIPTION = "Return the structured result by calling this tool."
-type GenerateObjectBase = Omit<RequestInput, "tools" | "toolChoice">
+type GenerateObjectBase = Omit<RequestInput, "tools" | "toolChoice" | "responseFormat">
 export class GenerateObjectResponse<T> {
  constructor(
@@ -1,5 +1,4 @@
 import { Effect, Schema } from "effect"
 import { Tool } from "@opencode-ai/schema/tool"
 import { Route } from "../route/client"
 import { Auth } from "../route/auth"
 import { Endpoint } from "../route/endpoint"
@@ -8,18 +7,16 @@ import { Protocol } from "../route/protocol"
 import {
  LLMError,
  LLMEvent,
  mergeJsonRecords,
  Usage,
  type CacheHint,
  type FinishReasonDetails,
  type FinishReason,
  type JsonSchema,
  type LLMRequest,
  type MediaPart,
  type ProviderOptions,
  type ProviderMetadata,
  type ToolCallPart,
  type ToolDefinition,
  type ToolContent,
  type ToolResultPart,
 } from "../schema"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
@@ -34,29 +31,6 @@ const MEDIA_MIMES = new Set<string>([...ProviderShared.IMAGE_MIMES, ...ProviderS
 export const DEFAULT_BASE_URL = "https://api.anthropic.com/v1"
 export const PATH = "/messages"
 export type ThinkingInput =
  | {
      readonly type: "adaptive"
      readonly display?: "summarized" | "omitted"
    }
  | {
      readonly type: "disabled"
    }
  | ({ readonly type: "enabled" } & (
      | { readonly budgetTokens: number; readonly budget_tokens?: number }
      | { readonly budgetTokens?: number; readonly budget_tokens: number }
    ))
 export interface OptionsInput {
  readonly [key: string]: unknown
  readonly thinking?: ThinkingInput
  readonly effort?: string
 }
 export type ProviderOptionsInput = ProviderOptions & {
  readonly anthropic?: OptionsInput
 }
 // =============================================================================
 // Request Body Schema
 // =============================================================================
@@ -101,15 +75,6 @@ const AnthropicThinkingBlock = Schema.Struct({
  cache_control: Schema.optional(AnthropicCacheControl),
 })
 // Safety-filtered thinking arrives as an opaque encrypted `data` payload with
 // no visible text. It must round-trip verbatim so multi-turn thinking + tool
 // use conversations keep their reasoning continuity.
 const AnthropicRedactedThinkingBlock = Schema.Struct({
  type: Schema.tag("redacted_thinking"),
  data: Schema.String,
  cache_control: Schema.optional(AnthropicCacheControl),
 })
 const AnthropicToolUseBlock = Schema.Struct({
  type: Schema.tag("tool_use"),
  id: Schema.String,
@@ -171,7 +136,6 @@ type AnthropicUserBlock = Schema.Schema.Type<typeof AnthropicUserBlock>
 const AnthropicAssistantBlock = Schema.Union([
  AnthropicTextBlock,
  AnthropicThinkingBlock,
  AnthropicRedactedThinkingBlock,
  AnthropicToolUseBlock,
  AnthropicServerToolUseBlock,
  AnthropicServerToolResultBlock,
@@ -195,7 +159,7 @@ const AnthropicTool = Schema.Struct({
 type AnthropicTool = Schema.Schema.Type<typeof AnthropicTool>
 const AnthropicToolChoice = Schema.Union([
-  Schema.Struct({ type: Schema.Literals(["auto", "any", "none"]) }),
+  Schema.Struct({ type: Schema.Literals(["auto", "any"]) }),
  Schema.Struct({ type: Schema.tag("tool"), name: Schema.String }),
 ])
@@ -235,27 +199,12 @@ const AnthropicBodyFields = {
 export const AnthropicMessagesBody = Schema.Struct(AnthropicBodyFields)
 export type AnthropicMessagesBody = Schema.Schema.Type<typeof AnthropicMessagesBody>
-const AnthropicUsage = Schema.StructWithRest(
+const AnthropicUsage = Schema.Struct({
-  Schema.Struct({
+  input_tokens: Schema.optional(Schema.Number),
-    input_tokens: Schema.optional(Schema.Number),
+  output_tokens: Schema.optional(Schema.Number),
-    output_tokens: Schema.optional(Schema.Number),
+  cache_creation_input_tokens: optionalNull(Schema.Number),
-    cache_creation_input_tokens: optionalNull(Schema.Number),
+  cache_read_input_tokens: optionalNull(Schema.Number),
-    cache_read_input_tokens: optionalNull(Schema.Number),
+})
    server_tool_use: optionalNull(
      Schema.StructWithRest(
        Schema.Struct({ web_search_requests: Schema.optional(Schema.Number) }),
        [Schema.Record(Schema.String, Schema.Unknown)],
      ),
    ),
    output_tokens_details: optionalNull(
      Schema.StructWithRest(
        Schema.Struct({ thinking_tokens: Schema.optional(Schema.Number) }),
        [Schema.Record(Schema.String, Schema.Unknown)],
      ),
    ),
  }),
  [Schema.Record(Schema.String, Schema.Unknown)],
 )
 type AnthropicUsage = Schema.Schema.Type<typeof AnthropicUsage>
 const AnthropicStreamBlock = Schema.Struct({
@@ -265,9 +214,6 @@ const AnthropicStreamBlock = Schema.Struct({
  text: Schema.optional(Schema.String),
  thinking: Schema.optional(Schema.String),
  signature: Schema.optional(Schema.String),
  // redacted_thinking blocks arrive whole in content_block_start with the
  // encrypted payload in `data`; there is no streaming delta sequence.
  data: Schema.optional(Schema.String),
  input: Schema.optional(Schema.Unknown),
  // *_tool_result blocks arrive whole as content_block_start (no streaming
  // delta) with the structured payload in `content` and the originating
@@ -305,12 +251,7 @@ type AnthropicEvent = Schema.Schema.Type<typeof AnthropicEvent>
 interface ParserState {
  readonly tools: ToolStream.State<number>
  readonly reasoningSignatures: Readonly<Record<number, string>>
  readonly usage?: Usage
  readonly pendingFinish?: {
    readonly reason: FinishReasonDetails
    readonly providerMetadata?: ProviderMetadata
  }
  readonly lifecycle: Lifecycle.State
 }
@@ -346,12 +287,6 @@ const signatureFromMetadata = (metadata: ProviderMetadata | undefined): string |
  return typeof anthropic.signature === "string" ? anthropic.signature : undefined
 }
 const redactedDataFromMetadata = (metadata: ProviderMetadata | undefined): string | undefined => {
  const anthropic = metadata?.anthropic
  if (!ProviderShared.isRecord(anthropic)) return undefined
  return typeof anthropic.redactedData === "string" ? anthropic.redactedData : undefined
 }
 const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSchema: JsonSchema): AnthropicTool => ({
  name: tool.name,
  description: tool.description,
@@ -362,7 +297,7 @@ const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSc
 const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
  ProviderShared.matchToolChoice("Anthropic Messages", toolChoice, {
    auto: () => ({ type: "auto" as const }),
-    none: () => ({ type: "none" as const }),
+    none: () => undefined,
    required: () => ({ type: "any" as const }),
    tool: (name) => ({ type: "tool" as const, name }),
  })
@@ -395,10 +330,7 @@ const lowerServerToolResult = Effect.fn("AnthropicMessages.lowerServerToolResult
  const wireType = serverToolResultType(part.name)
  if (!wireType)
    return yield* invalid(`Anthropic Messages does not know how to round-trip server tool result for ${part.name}`)
-  // Prefer the provider-owned replay payload; fall back to the result value for
+  return { type: wireType, tool_use_id: part.id, content: part.result.value } satisfies AnthropicServerToolResultBlock
  // histories constructed directly from provider events.
  const payload = part.providerMetadata?.anthropic?.["result"] ?? part.result.value
  return { type: wireType, tool_use_id: part.id, content: payload } satisfies AnthropicServerToolResultBlock
 })
 const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (part: MediaPart) {
@@ -425,7 +357,7 @@ const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (part: Me
 // Tool results may carry structured text, images, and documents. Keep media as provider-native
 // content instead of JSON-stringifying base64 into a prompt string.
 const lowerToolResultContentItem = Effect.fn("AnthropicMessages.lowerToolResultContentItem")(function* (
-  item: Tool.Content,
+  item: ToolContent,
 ) {
  if (item.type === "text") return { type: "text" as const, text: item.text } satisfies AnthropicTextBlock
  return yield* lowerMedia({ type: "media", mediaType: item.mime, data: item.uri, filename: item.name })
@@ -436,7 +368,7 @@ const lowerToolResultContent = Effect.fn("AnthropicMessages.lowerToolResultConte
  // with existing cassettes and provider expectations.
  if (part.result.type !== "content") return ProviderShared.toolResultText(part)
  // Preserve the narrowed array element type when compiled through a consumer package.
-  const content: ReadonlyArray<Tool.Content> = part.result.value
+  const content: ReadonlyArray<ToolContent> = part.result.value
  return yield* Effect.forEach(content, lowerToolResultContentItem)
 })
@@ -537,16 +469,11 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
          continue
        }
        if (part.type === "reasoning") {
-          // Mirrors Vercel's @ai-sdk/anthropic: a signature marks visible
+          content.push({
-          // thinking; only signature-less parts carrying redactedData
+            type: "thinking",
-          // round-trip as opaque redacted_thinking blocks.
+            thinking: part.text,
-          const signature = part.encrypted ?? signatureFromMetadata(part.providerMetadata)
+            signature: part.encrypted ?? signatureFromMetadata(part.providerMetadata),
-          const redactedData = redactedDataFromMetadata(part.providerMetadata)
+          })
          if (signature === undefined && redactedData !== undefined) {
            content.push({ type: "redacted_thinking", data: redactedData })
            continue
          }
          content.push({ type: "thinking", thinking: part.text, signature })
          continue
        }
        if (part.type === "tool-call") {
@@ -583,39 +510,39 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
  return messages
 })
-const resolveOptions = Effect.fn("AnthropicMessages.resolveOptions")(function* (request: LLMRequest) {
+const anthropicOptions = (request: LLMRequest) => request.providerOptions?.anthropic
  const input = request.providerOptions?.anthropic
  return {
    thinking: yield* resolveThinking(input?.thinking),
    effort: typeof input?.effort === "string" ? input.effort : undefined,
  }
 })
-const resolveThinking = Effect.fn("AnthropicMessages.resolveThinking")(function* (input: unknown) {
+const lowerThinking = Effect.fn("AnthropicMessages.lowerThinking")(function* (request: LLMRequest) {
-  if (!ProviderShared.isRecord(input)) return undefined
+  const thinking = anthropicOptions(request)?.thinking
-  if (input.type === "adaptive") {
+  if (!ProviderShared.isRecord(thinking)) return undefined
  if (thinking.type === "adaptive") {
    const display =
-      input.display === "summarized"
+      thinking.display === "summarized"
        ? ("summarized" as const)
-        : input.display === "omitted"
+        : thinking.display === "omitted"
          ? ("omitted" as const)
          : undefined
    return { type: "adaptive" as const, ...(display === undefined ? {} : { display }) }
  }
-  if (input.type === "disabled") return { type: "disabled" as const }
+  if (thinking.type === "disabled") return { type: "disabled" as const }
-  if (input.type !== "enabled") return undefined
+  if (thinking.type !== "enabled") return undefined
  const budget =
-    typeof input.budgetTokens === "number"
+    typeof thinking.budgetTokens === "number"
-      ? input.budgetTokens
+      ? thinking.budgetTokens
-      : typeof input.budget_tokens === "number"
+      : typeof thinking.budget_tokens === "number"
-        ? input.budget_tokens
+        ? thinking.budget_tokens
        : undefined
-  if (budget === undefined)
+  if (budget === undefined) return yield* invalid("Anthropic thinking provider option requires budgetTokens")
    return yield* ProviderShared.invalidRequest("Anthropic thinking provider option requires budgetTokens")
  return { type: "enabled" as const, budget_tokens: budget }
 })
 const outputConfig = (request: LLMRequest) => {
  const effort = anthropicOptions(request)?.effort
  return typeof effort === "string" ? { effort } : undefined
 }
 const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (request: LLMRequest) {
  const toolChoice = request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined
  const generation = request.generation
  const toolSchemaCompatibility = request.model.compatibility?.toolSchema
  const outputLimit = request.model.defaults?.limits?.output ?? request.model.route.defaults.limits?.output ?? 4096
@@ -624,7 +551,7 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
  // over-mark we keep their tool hints and shed the message-tail ones first.
  const breakpoints = Cache.newBreakpoints(ANTHROPIC_BREAKPOINT_CAP)
  const tools =
-    request.tools.length === 0
+    request.tools.length === 0 || request.toolChoice?.type === "none"
      ? undefined
      : request.tools.map((tool) =>
          lowerTool(
@@ -633,8 +560,6 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
            ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility),
          ),
        )
  // Anthropic rejects tool_choice when tools are absent; "none" is only meaningful with tools present.
  const toolChoice = tools === undefined || !request.toolChoice ? undefined : yield* lowerToolChoice(request.toolChoice)
  const system =
    request.system.length === 0
      ? undefined
@@ -649,7 +574,6 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
      `Anthropic Messages: dropped ${breakpoints.dropped} cache breakpoint(s); the API allows at most ${ANTHROPIC_BREAKPOINT_CAP} per request.`,
    )
  }
  const options = yield* resolveOptions(request)
  return {
    model: request.model.id,
    system,
@@ -662,8 +586,8 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
    top_p: generation?.topP,
    top_k: generation?.topK,
    stop_sequences: generation?.stop,
-    thinking: options.thinking,
+    thinking: yield* lowerThinking(request),
-    output_config: options.effort === undefined ? undefined : { effort: options.effort },
+    output_config: outputConfig(request),
  }
 })
@@ -672,7 +596,7 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
 // =============================================================================
 const mapFinishReason = (reason: string | null | undefined): FinishReason => {
  if (reason === "end_turn" || reason === "stop_sequence" || reason === "pause_turn") return "stop"
-  if (reason === "max_tokens" || reason === "model_context_window_exceeded") return "length"
+  if (reason === "max_tokens") return "length"
  if (reason === "tool_use") return "tool-calls"
  if (reason === "refusal") return "content-filter"
  return "unknown"
@@ -682,8 +606,9 @@ const mapFinishReason = (reason: string | null | undefined): FinishReason => {
 // `input_tokens` is the *non-cached* count per the Messages API docs, with
 // cache reads and writes as separate fields. We sum them to derive the
 // inclusive `inputTokens` the rest of the contract expects. Extended
-// thinking tokens are included in `output_tokens`; newer responses also
+// thinking tokens are *not* broken out by Anthropic — they're billed as
-// expose that subset through `output_tokens_details.thinking_tokens`.
+// part of `output_tokens`, so `reasoningTokens` stays `undefined` and
 // `outputTokens` carries the combined total.
 const mapUsage = (usage: AnthropicUsage | undefined): Usage | undefined => {
  if (!usage) return undefined
  const nonCached = usage.input_tokens
@@ -696,7 +621,6 @@ const mapUsage = (usage: AnthropicUsage | undefined): Usage | undefined => {
    nonCachedInputTokens: nonCached,
    cacheReadInputTokens: cacheRead,
    cacheWriteInputTokens: cacheWrite,
    reasoningTokens: usage.output_tokens_details?.thinking_tokens,
    totalTokens: ProviderShared.totalTokens(inputTokens, usage.output_tokens, undefined),
    providerMetadata: { anthropic: usage },
  })
@@ -715,18 +639,18 @@ const mergeUsage = (left: Usage | undefined, right: Usage | undefined) => {
  const cacheWriteInputTokens = right.cacheWriteInputTokens ?? left.cacheWriteInputTokens
  const inputTokens = ProviderShared.sumTokens(nonCachedInputTokens, cacheReadInputTokens, cacheWriteInputTokens)
  const outputTokens = right.outputTokens ?? left.outputTokens
  const reasoningTokens = right.reasoningTokens ?? left.reasoningTokens
  return new Usage({
    inputTokens,
    outputTokens,
    nonCachedInputTokens,
    cacheReadInputTokens,
    cacheWriteInputTokens,
    reasoningTokens,
    totalTokens: ProviderShared.totalTokens(inputTokens, outputTokens, undefined),
    providerMetadata: {
-      anthropic:
+      anthropic: {
-        mergeJsonRecords(left.providerMetadata?.["anthropic"], right.providerMetadata?.["anthropic"]) ?? {},
+        ...left.providerMetadata?.["anthropic"],
        ...right.providerMetadata?.["anthropic"],
      },
    },
  })
 }
@@ -756,9 +680,7 @@ const serverToolResultEvent = (block: NonNullable<AnthropicEvent["content_block"
    name: SERVER_TOOL_RESULT_NAMES[block.type],
    result: isError ? { type: "error", value: block.content } : { type: "json", value: block.content },
    providerExecuted: true,
-    // The complete payload is irreducible provider replay state: subsequent
+    providerMetadata: anthropicMetadata({ blockType: block.type }),
    // stateless requests must round-trip the typed result block verbatim.
    providerMetadata: anthropicMetadata({ blockType: block.type, result: block.content }),
  })
 }
@@ -785,10 +707,6 @@ const onContentBlockStart = (state: ParserState, event: AnthropicEvent): StepRes
        tools: ToolStream.start(state.tools, event.index, {
          id: block.id ?? String(event.index),
          name: block.name ?? "",
          input:
            block.input !== undefined && (!ProviderShared.isRecord(block.input) || Object.keys(block.input).length > 0)
              ? ProviderShared.encodeJson(block.input)
              : undefined,
          providerExecuted: block.type === "server_tool_use",
        }),
      },
@@ -803,50 +721,20 @@ const onContentBlockStart = (state: ParserState, event: AnthropicEvent): StepRes
    ]
  }
-  if (block.type === "text" && block.text !== undefined) {
+  if (block.type === "text" && block.text) {
    const events: LLMEvent[] = []
    const id = `text-${event.index ?? 0}`
    const lifecycle = Lifecycle.textStart(state.lifecycle, events, id)
    return [
-      { ...state, lifecycle: block.text ? Lifecycle.textDelta(lifecycle, events, id, block.text) : lifecycle },
+      { ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, `text-${event.index ?? 0}`, block.text) },
      events,
    ]
  }
-  if (block.type === "thinking" && block.thinking !== undefined) {
+  if (block.type === "thinking" && block.thinking) {
    const events: LLMEvent[] = []
    const id = `reasoning-${event.index ?? 0}`
    const providerMetadata = block.signature === undefined ? undefined : anthropicMetadata({ signature: block.signature })
    const lifecycle = Lifecycle.reasoningStart(state.lifecycle, events, id, providerMetadata)
    return [
      {
        ...state,
        lifecycle: block.thinking
          ? Lifecycle.reasoningDelta(lifecycle, events, id, block.thinking, providerMetadata)
          : lifecycle,
        reasoningSignatures:
          event.index === undefined || block.signature === undefined
            ? state.reasoningSignatures
            : { ...state.reasoningSignatures, [event.index]: block.signature },
      },
      events,
    ]
  }
  // Redacted thinking surfaces as an empty reasoning part carrying the opaque
  // payload as `redactedData` metadata (same model as Vercel's
  // @ai-sdk/anthropic). The existing content_block_stop closes the part.
  if (block.type === "redacted_thinking" && block.data !== undefined) {
    const events: LLMEvent[] = []
    return [
      {
        ...state,
-        lifecycle: Lifecycle.reasoningStart(
+        lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${event.index ?? 0}`, block.thinking),
          state.lifecycle,
          events,
          `reasoning-${event.index ?? 0}`,
          anthropicMetadata({ redactedData: block.data }),
        ),
      },
      events,
    ]
@@ -884,13 +772,18 @@ const onContentBlockDelta = Effect.fn("AnthropicMessages.onContentBlockDelta")(f
  }
  if (delta?.type === "signature_delta" && delta.signature) {
-    const index = event.index ?? 0
+    const events: LLMEvent[] = []
    return [
      {
        ...state,
-        reasoningSignatures: { ...state.reasoningSignatures, [index]: delta.signature },
+        lifecycle: Lifecycle.reasoningEnd(
          state.lifecycle,
          events,
          `reasoning-${event.index ?? 0}`,
          anthropicMetadata({ signature: delta.signature }),
        ),
      },
-      NO_EVENTS,
+      events,
    ] satisfies StepResult
  }
@@ -921,53 +814,28 @@ const onContentBlockStop = Effect.fn("AnthropicMessages.onContentBlockStop")(fun
  const result = yield* ToolStream.finish(ADAPTER, state.tools, event.index)
  const events: LLMEvent[] = []
  const resultEvents = result.events ?? []
  const signature = state.reasoningSignatures[event.index]
  const lifecycle = resultEvents.length
    ? Lifecycle.stepStart(state.lifecycle, events)
    : Lifecycle.reasoningEnd(
        Lifecycle.textEnd(state.lifecycle, events, `text-${event.index}`),
        events,
        `reasoning-${event.index}`,
        signature === undefined ? undefined : anthropicMetadata({ signature }),
      )
  events.push(...resultEvents)
-  const reasoningSignatures = { ...state.reasoningSignatures }
+  return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult
  delete reasoningSignatures[event.index]
  return [{ ...state, lifecycle, tools: result.tools, reasoningSignatures }, events] satisfies StepResult
 })
 const onMessageDelta = (state: ParserState, event: AnthropicEvent): StepResult => {
  const usage = mergeUsage(state.usage, mapUsage(event.usage))
  return [
    {
      ...state,
      usage,
      pendingFinish: {
        reason: {
          normalized: mapFinishReason(event.delta?.stop_reason),
          raw: event.delta?.stop_reason ?? undefined,
        },
        providerMetadata:
          event.delta?.stop_sequence === null || event.delta?.stop_sequence === undefined
            ? undefined
            : anthropicMetadata({ stopSequence: event.delta.stop_sequence }),
      },
    },
    NO_EVENTS,
  ]
 }
 const onMessageStop = (state: ParserState): StepResult => {
  const events: LLMEvent[] = []
  const lifecycle = Lifecycle.finish(state.lifecycle, events, {
-    reason: state.pendingFinish?.reason ?? {
+    reason: mapFinishReason(event.delta?.stop_reason),
-      normalized: "unknown",
+    usage,
-      raw: undefined,
+    providerMetadata: event.delta?.stop_sequence
-    },
+      ? anthropicMetadata({ stopSequence: event.delta.stop_sequence })
-    usage: state.usage,
+      : undefined,
    providerMetadata: state.pendingFinish?.providerMetadata,
  })
-  return [{ ...state, lifecycle }, events]
+  return [{ ...state, lifecycle, usage }, events]
 }
 // Prefix `error.type` so overloads, rate limits, and quota errors are visible
@@ -992,7 +860,6 @@ const step = (state: ParserState, event: AnthropicEvent) => {
  if (event.type === "content_block_delta") return onContentBlockDelta(state, event)
  if (event.type === "content_block_stop") return onContentBlockStop(state, event)
  if (event.type === "message_delta") return Effect.succeed(onMessageDelta(state, event))
  if (event.type === "message_stop") return Effect.succeed(onMessageStop(state))
  if (event.type === "error") return onError(event)
  return Effect.succeed<StepResult>([state, NO_EVENTS])
 }
@@ -1013,11 +880,7 @@ export const protocol = Protocol.make({
  },
  stream: {
    event: Protocol.jsonEvent(AnthropicEvent),
-    initial: () => ({
+    initial: () => ({ tools: ToolStream.empty<number>(), lifecycle: Lifecycle.initial() }),
      tools: ToolStream.empty<number>(),
      reasoningSignatures: {},
      lifecycle: Lifecycle.initial(),
    }),
    step,
  },
 })
@@ -8,7 +8,6 @@ import {
  Usage,
  type CacheHint,
  type FinishReason,
  type FinishReasonDetails,
  type JsonSchema,
  type LLMRequest,
  type ModelToolSchemaCompatibility,
@@ -66,15 +65,14 @@ const BedrockToolResultBlock = Schema.Struct({
 type BedrockToolResultBlock = Schema.Schema.Type<typeof BedrockToolResultBlock>
 const BedrockReasoningBlock = Schema.Struct({
-  reasoningContent: Schema.Union([
+  reasoningContent: Schema.Struct({
-    Schema.Struct({
+    reasoningText: Schema.optional(
-      reasoningText: Schema.Struct({
+      Schema.Struct({
        text: Schema.String,
        signature: Schema.optional(Schema.String),
      }),
-    }),
+    ),
-    Schema.Struct({ redactedContent: Schema.String }),
+  }),
  ]),
 })
 const BedrockUserBlock = Schema.Union([
@@ -155,12 +153,6 @@ const BedrockUsageSchema = Schema.Struct({
 })
 type BedrockUsageSchema = Schema.Schema.Type<typeof BedrockUsageSchema>
 const BedrockStreamException = Schema.Struct({
  message: Schema.optional(Schema.String),
  originalMessage: Schema.optional(Schema.String),
  originalStatusCode: Schema.optional(Schema.Number),
 })
 // Streaming event shape — the AWS event stream wraps each JSON payload by its
 // `:event-type` header (e.g. `messageStart`, `contentBlockDelta`). We
 // reconstruct that wrapping in `decodeFrames` below so the event schema can
@@ -188,11 +180,6 @@ const BedrockEvent = Schema.Struct({
            Schema.Struct({
              text: Schema.optional(Schema.String),
              signature: Schema.optional(Schema.String),
              // Blob fields in Bedrock's JSON event stream are base64 strings.
              redactedContent: Schema.optional(Schema.String),
              // Vercel's Bedrock provider exposes the same delta under
              // Anthropic's shorter `data` spelling.
              data: Schema.optional(Schema.String),
            }),
          ),
        }),
@@ -212,11 +199,11 @@ const BedrockEvent = Schema.Struct({
      metrics: Schema.optional(Schema.Unknown),
    }),
  ),
-  internalServerException: Schema.optional(BedrockStreamException),
+  internalServerException: Schema.optional(Schema.Struct({ message: Schema.String })),
-  modelStreamErrorException: Schema.optional(BedrockStreamException),
+  modelStreamErrorException: Schema.optional(Schema.Struct({ message: Schema.String })),
-  validationException: Schema.optional(BedrockStreamException),
+  validationException: Schema.optional(Schema.Struct({ message: Schema.String })),
-  throttlingException: Schema.optional(BedrockStreamException),
+  throttlingException: Schema.optional(Schema.Struct({ message: Schema.String })),
-  serviceUnavailableException: Schema.optional(BedrockStreamException),
+  serviceUnavailableException: Schema.optional(Schema.Struct({ message: Schema.String })),
 })
 type BedrockEvent = Schema.Schema.Type<typeof BedrockEvent>
@@ -272,13 +259,6 @@ const reasoningSignature = (part: ReasoningPart) => {
  )
 }
 const reasoningRedactedData = (part: ReasoningPart) => {
  const bedrock = part.providerMetadata?.bedrock
  return ProviderShared.isRecord(bedrock) && typeof bedrock.redactedData === "string"
    ? bedrock.redactedData
    : undefined
 }
 const lowerToolCall = (part: ToolCallPart): BedrockToolUseBlock => ({
  toolUse: {
    toolUseId: part.id,
@@ -368,13 +348,11 @@ const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
          continue
        }
        if (part.type === "reasoning") {
-          const signature = reasoningSignature(part)
+          content.push({
-          const redactedData = reasoningRedactedData(part)
+            reasoningContent: {
-          if (signature === undefined && redactedData !== undefined) {
+              reasoningText: { text: part.text, signature: reasoningSignature(part) },
-            content.push({ reasoningContent: { redactedContent: redactedData } })
+            },
-            continue
+          })
          }
          content.push({ reasoningContent: { reasoningText: { text: part.text, signature } } })
          continue
        }
        if (part.type === "tool-call") {
@@ -414,13 +392,8 @@ const fromRequest = Effect.fn("BedrockConverse.fromRequest")(function* (request:
  // tools → system → messages order to favour the highest-impact prefixes.
  const breakpoints = BedrockCache.breakpoints()
  const toolConfig =
-    request.tools.length > 0
+    request.tools.length > 0 && request.toolChoice?.type !== "none"
-      ? {
+      ? { tools: lowerTools(request.model.compatibility?.toolSchema, breakpoints, request.tools), toolChoice }
          tools: lowerTools(request.model.compatibility?.toolSchema, breakpoints, request.tools),
          // Converse has no native "none". Keep definitions stable for prompt
          // caching and omit only the unsupported choice.
          toolChoice,
        }
      : undefined
  const system = request.system.length === 0 ? undefined : lowerSystem(breakpoints, request.system)
  const messages = yield* lowerMessages(request, breakpoints)
@@ -457,10 +430,9 @@ const fromRequest = Effect.fn("BedrockConverse.fromRequest")(function* (request:
 // =============================================================================
 const mapFinishReason = (reason: string): FinishReason => {
  if (reason === "end_turn" || reason === "stop_sequence") return "stop"
-  if (reason === "max_tokens" || reason === "model_context_window_exceeded") return "length"
+  if (reason === "max_tokens") return "length"
  if (reason === "tool_use") return "tool-calls"
  if (reason === "content_filtered" || reason === "guardrail_intervened") return "content-filter"
  if (reason === "malformed_model_output" || reason === "malformed_tool_use") return "error"
  return "unknown"
 }
@@ -489,7 +461,7 @@ interface ParserState {
  // Bedrock splits the finish into `messageStop` (carries `stopReason`) and
  // `metadata` (carries usage). Hold the terminal event in state so `onHalt`
  // can emit exactly one finish after both chunks have had a chance to arrive.
-  readonly pendingFinish: { readonly reason: FinishReasonDetails; readonly usage?: Usage } | undefined
+  readonly pendingFinish: { readonly reason: FinishReason; readonly usage?: Usage } | undefined
  readonly hasToolCalls: boolean
  readonly lifecycle: Lifecycle.State
  readonly reasoningSignatures: Readonly<Record<number, string>>
@@ -540,26 +512,12 @@ const step = (state: ParserState, event: BedrockEvent) =>
      const index = event.contentBlockDelta.contentBlockIndex
      const reasoning = event.contentBlockDelta.delta.reasoningContent
      const events: LLMEvent[] = []
      const redactedData = reasoning.redactedContent ?? reasoning.data
      const providerMetadata = reasoning.signature
        ? bedrockMetadata({ signature: reasoning.signature })
        : redactedData !== undefined
          ? bedrockMetadata({ redactedData })
          : undefined
      const lifecycle =
        reasoning.text !== undefined || providerMetadata !== undefined
          ? Lifecycle.reasoningDelta(
              state.lifecycle,
              events,
              `reasoning-${index}`,
              reasoning.text ?? "",
              providerMetadata,
            )
          : state.lifecycle
      return [
        {
          ...state,
-          lifecycle,
+          lifecycle: reasoning.text
            ? Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${index}`, reasoning.text)
            : state.lifecycle,
          reasoningSignatures: reasoning.signature
            ? { ...state.reasoningSignatures, [index]: reasoning.signature }
            : state.reasoningSignatures,
@@ -620,30 +578,15 @@ const step = (state: ParserState, event: BedrockEvent) =>
      return [
        {
          ...state,
-          pendingFinish: {
+          pendingFinish: { reason: mapFinishReason(event.messageStop.stopReason), usage: state.pendingFinish?.usage },
            reason: {
              normalized: mapFinishReason(event.messageStop.stopReason),
              raw: event.messageStop.stopReason,
            },
            usage: state.pendingFinish?.usage,
          },
        },
        [],
      ] as const
    }
    if (event.metadata) {
-      const usage = mapUsage(event.metadata.usage) ?? state.pendingFinish?.usage
+      const usage = mapUsage(event.metadata.usage)
-      return [
+      return [{ ...state, pendingFinish: { reason: state.pendingFinish?.reason ?? "stop", usage } }, []] as const
        {
          ...state,
          pendingFinish: {
            reason: state.pendingFinish?.reason ?? { normalized: "stop" },
            usage,
          },
        },
        [],
      ] as const
    }
    const exception = (
@@ -660,7 +603,7 @@ const step = (state: ParserState, event: BedrockEvent) =>
        module: ADAPTER,
        method: "stream",
        reason: classifyProviderFailure({
-          message: exception[1]?.message ?? exception[1]?.originalMessage ?? "Bedrock Converse stream error",
+          message: exception[1]?.message ?? "Bedrock Converse stream error",
          code: exception[0],
        }),
      })
@@ -676,13 +619,8 @@ const onHalt = (state: ParserState): ReadonlyArray<LLMEvent> =>
    ? (() => {
        const events: LLMEvent[] = []
        Lifecycle.finish(state.lifecycle, events, {
-          reason: {
+          reason:
-            ...state.pendingFinish.reason,
+            state.pendingFinish.reason === "stop" && state.hasToolCalls ? "tool-calls" : state.pendingFinish.reason,
            normalized:
              state.pendingFinish.reason.normalized === "stop" && state.hasToolCalls
                ? "tool-calls"
                : state.pendingFinish.reason.normalized,
          },
          usage: state.pendingFinish.usage,
        })
        return events
@@ -53,22 +53,8 @@ const consumeFrames = (route: string) => (state: FrameBufferState, chunk: Uint8A
      })
      cursor = { buffer: cursor.buffer, offset: cursor.offset + totalLength }
-      const messageType = decoded.headers[":message-type"]?.value
+      if (decoded.headers[":message-type"]?.value !== "event") continue
-      if (messageType === "error") {
+      const eventType = decoded.headers[":event-type"]?.value
        const code = decoded.headers[":error-code"]?.value
        const message = decoded.headers[":error-message"]?.value
        return yield* ProviderShared.eventError(
          route,
          [code, message].filter((value): value is string => typeof value === "string").join(": ") ||
            "Bedrock Converse event-stream error",
        )
      }
      const eventType =
        messageType === "event"
          ? decoded.headers[":event-type"]?.value
          : messageType === "exception"
            ? decoded.headers[":exception-type"]?.value
            : undefined
      if (typeof eventType !== "string") continue
      const payload = utf8.decode(decoded.body)
      if (!payload) continue
@@ -1,5 +1,4 @@
 import { Effect, Schema } from "effect"
 import { Tool } from "@opencode-ai/schema/tool"
 import { Route } from "../route/client"
 import { Auth } from "../route/auth"
 import { Endpoint } from "../route/endpoint"
@@ -12,11 +11,11 @@ import {
  type JsonSchema,
  type LLMRequest,
  type MediaPart,
  type ProviderOptions,
  type ProviderMetadata,
  type TextPart,
  type ToolCallPart,
  type ToolDefinition,
  type ToolContent,
 } from "../schema"
 import { JsonObject, optionalArray, ProviderShared } from "./shared"
 import { GeminiToolSchema } from "./utils/gemini-tool-schema"
@@ -27,18 +26,6 @@ const ADAPTER = "gemini"
 const MEDIA_MIMES = new Set<string>(ProviderShared.MEDIA_MIMES)
 export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
 export interface OptionsInput {
  readonly [key: string]: unknown
  readonly thinkingConfig?: {
    readonly thinkingBudget?: number
    readonly includeThoughts?: boolean
  }
 }
 export type ProviderOptionsInput = ProviderOptions & {
  readonly gemini?: OptionsInput
 }
 // =============================================================================
 // Request Body Schema
 // =============================================================================
@@ -216,9 +203,7 @@ const thoughtSignature = (providerMetadata: ProviderMetadata | undefined) => {
 const functionCallId = (providerMetadata: ProviderMetadata | undefined) => {
  const google = providerMetadata?.google
-  return ProviderShared.isRecord(google) && typeof google.functionCallId === "string"
+  return ProviderShared.isRecord(google) && typeof google.functionCallId === "string" ? google.functionCallId : undefined
    ? google.functionCallId
    : undefined
 }
 const lowerToolCall = (part: ToolCallPart) => ({
@@ -289,7 +274,7 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
        })
        continue
      }
-      const content: ReadonlyArray<Tool.Content> = part.result.value
+      const content: ReadonlyArray<ToolContent> = part.result.value
      const text = content.filter((item) => item.type === "text").map((item) => item.text)
      const media: GeminiInlineDataPart[] = []
      for (const item of content) {
@@ -315,22 +300,21 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
  return contents
 })
-const resolveOptions = (request: LLMRequest) => {
+const geminiOptions = (request: LLMRequest) => request.providerOptions?.gemini
-  const value = request.providerOptions?.gemini?.thinkingConfig
+
-  if (!ProviderShared.isRecord(value)) return {}
+const thinkingConfig = (request: LLMRequest) => {
-  const thinkingConfig = {
+  const value = geminiOptions(request)?.thinkingConfig
  if (!ProviderShared.isRecord(value)) return undefined
  const result = {
    thinkingBudget: typeof value.thinkingBudget === "number" ? value.thinkingBudget : undefined,
    includeThoughts: typeof value.includeThoughts === "boolean" ? value.includeThoughts : undefined,
  }
-  return {
+  return Object.values(result).some((item) => item !== undefined) ? result : undefined
    thinkingConfig: Object.values(thinkingConfig).some((item) => item !== undefined) ? thinkingConfig : undefined,
  }
 }
 const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMRequest) {
-  const hasTools = request.tools.length > 0
+  const toolsEnabled = request.tools.length > 0 && request.toolChoice?.type !== "none"
  const generation = request.generation
  const options = resolveOptions(request)
  const toolSchemaCompatibility = request.model.compatibility?.toolSchema
  const generationConfig = {
    maxOutputTokens: generation?.maxTokens,
@@ -338,14 +322,14 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
    topP: generation?.topP,
    topK: generation?.topK,
    stopSequences: generation?.stop,
-    thinkingConfig: options.thinkingConfig,
+    thinkingConfig: thinkingConfig(request),
  }
  return {
    contents: yield* lowerMessages(request),
    systemInstruction:
      request.system.length === 0 ? undefined : { parts: [{ text: ProviderShared.joinText(request.system) }] },
-    tools: hasTools
+    tools: toolsEnabled
      ? [
          {
            functionDeclarations: request.tools.map((tool) =>
@@ -354,7 +338,7 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
          },
        ]
      : undefined,
-    toolConfig: hasTools && request.toolChoice ? yield* lowerToolConfig(request.toolChoice) : undefined,
+    toolConfig: toolsEnabled && request.toolChoice ? yield* lowerToolConfig(request.toolChoice) : undefined,
    generationConfig: Object.values(generationConfig).some((value) => value !== undefined)
      ? generationConfig
      : undefined,
@@ -398,22 +382,10 @@ const mapFinishReason = (finishReason: string | undefined, hasToolCalls: boolean
    finishReason === "SAFETY" ||
    finishReason === "BLOCKLIST" ||
    finishReason === "PROHIBITED_CONTENT" ||
-    finishReason === "SPII" ||
+    finishReason === "SPII"
    finishReason === "MODEL_ARMOR" ||
    finishReason === "IMAGE_PROHIBITED_CONTENT" ||
    finishReason === "IMAGE_RECITATION" ||
    finishReason === "LANGUAGE"
  )
    return "content-filter"
-  if (
+  if (finishReason === "MALFORMED_FUNCTION_CALL") return "error"
    finishReason === "MALFORMED_FUNCTION_CALL" ||
    finishReason === "UNEXPECTED_TOOL_CALL" ||
    finishReason === "NO_IMAGE" ||
    finishReason === "TOO_MANY_TOOL_CALLS" ||
    finishReason === "MISSING_THOUGHT_SIGNATURE" ||
    finishReason === "MALFORMED_RESPONSE"
  )
    return "error"
  return "unknown"
 }
@@ -430,10 +402,7 @@ const finish = (state: ParserState): ReadonlyArray<LLMEvent> =>
            )
          : state.lifecycle
        Lifecycle.finish(lifecycle, events, {
-          reason: {
+          reason: mapFinishReason(state.finishReason, state.hasToolCalls),
            normalized: mapFinishReason(state.finishReason, state.hasToolCalls),
            raw: state.finishReason,
          },
          usage: state.usage,
        })
        return events
@@ -6,4 +6,3 @@ export * as OpenAIImages from "./openai-images"
 export * as OpenAICompatibleChat from "./openai-compatible-chat"
 export * as OpenAICompatibleResponses from "./openai-compatible-responses"
 export * as OpenAIResponses from "./openai-responses"
 export * as OpenResponses from "./open-responses"
@@ -1,16 +1,13 @@
 import { Effect, Schema } from "effect"
 import { Tool } from "@opencode-ai/schema/tool"
 import { Route } from "../route/client"
 import { Auth } from "../route/auth"
 import { Endpoint } from "../route/endpoint"
 import { HttpTransport } from "../route/transport"
 import { Protocol } from "../route/protocol"
 import {
  LLMError,
  LLMEvent,
  Usage,
  type FinishReason,
  type FinishReasonDetails,
  type JsonSchema,
  type LLMRequest,
  type MediaPart,
@@ -18,8 +15,8 @@ import {
  type TextPart,
  type ToolCallPart,
  type ToolDefinition,
  type ToolContent,
 } from "../schema"
 import { classifyProviderFailure } from "../provider-error"
 import { isRecord, JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
 import { OpenAIOptions } from "./utils/openai-options"
 import { Lifecycle } from "./utils/lifecycle"
@@ -131,7 +128,6 @@ const OpenAIChatUsage = Schema.Struct({
  prompt_tokens_details: optionalNull(
    Schema.Struct({
      cached_tokens: Schema.optional(Schema.Number),
      cache_write_tokens: Schema.optional(Schema.Number),
    }),
  ),
  completion_tokens_details: optionalNull(
@@ -168,18 +164,11 @@ const OpenAIChatDelta = Schema.StructWithRest(
 const OpenAIChatChoice = Schema.Struct({
  delta: optionalNull(OpenAIChatDelta),
  finish_reason: optionalNull(Schema.String),
  native_finish_reason: optionalNull(Schema.String),
 })
 const OpenAIChatError = Schema.Struct({
  code: optionalNull(Schema.Union([Schema.String, Schema.Number])),
  message: Schema.String,
 })
 export const OpenAIChatEvent = Schema.Struct({
-  choices: optionalNull(Schema.Array(OpenAIChatChoice)),
+  choices: Schema.Array(OpenAIChatChoice),
  usage: optionalNull(OpenAIChatUsage),
  error: optionalNull(OpenAIChatError),
 })
 export type OpenAIChatEvent = Schema.Schema.Type<typeof OpenAIChatEvent>
 type OpenAIChatRequestMessage = LLMRequest["messages"][number]
@@ -195,7 +184,7 @@ export interface ParserState {
  readonly pendingTools: Partial<Record<number, PendingToolDelta>>
  readonly toolCallEvents: ReadonlyArray<LLMEvent>
  readonly usage?: Usage
-  readonly finishReason?: FinishReasonDetails
+  readonly finishReason?: FinishReason
  readonly lifecycle: Lifecycle.State
  readonly reasoningField?: string
  readonly reasoningDetails: Array<unknown>
@@ -335,7 +324,7 @@ const lowerToolMessages = Effect.fn("OpenAIChat.lowerToolMessages")(function* (m
      messages.push({ role: "tool", tool_call_id: part.id, content: ProviderShared.toolResultText(part) })
      continue
    }
-    const content: ReadonlyArray<Tool.Content> = part.result.value
+    const content: ReadonlyArray<ToolContent> = part.result.value
    const text = content.filter((item) => item.type === "text").map((item) => item.text)
    messages.push({ role: "tool", tool_call_id: part.id, content: text.join("\n") })
    const files = content.filter((item) => item.type === "file")
@@ -397,13 +386,14 @@ const lowerMessages = Effect.fn("OpenAIChat.lowerMessages")(function* (request:
  return messages
 })
-const lowerOptions = (request: LLMRequest) => {
+const lowerOptions = Effect.fn("OpenAIChat.lowerOptions")(function* (request: LLMRequest) {
-  const options = OpenAIOptions.resolve(request)
+  const store = OpenAIOptions.store(request)
  const reasoningEffort = OpenAIOptions.reasoningEffort(request)
  return {
-    ...(options.store !== undefined ? { store: options.store } : {}),
+    ...(store !== undefined ? { store } : {}),
-    ...(options.reasoningEffort ? { reasoning_effort: options.reasoningEffort } : {}),
+    ...(reasoningEffort ? { reasoning_effort: reasoningEffort } : {}),
  }
-}
+})
 const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (request: LLMRequest) {
  // `fromRequest` returns the provider body only. Endpoint, auth, framing,
@@ -434,7 +424,7 @@ const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (request: LLMR
    presence_penalty: generation?.presencePenalty,
    seed: generation?.seed,
    stop: generation?.stop,
-    ...lowerOptions(request),
+    ...(yield* lowerOptions(request)),
  }
 })
@@ -449,27 +439,24 @@ const mapFinishReason = (reason: string | null | undefined): FinishReason => {
  if (reason === "length") return "length"
  if (reason === "content_filter") return "content-filter"
  if (reason === "function_call" || reason === "tool_calls") return "tool-calls"
  if (reason === "error") return "error"
  return "unknown"
 }
 // OpenAI Chat reports `prompt_tokens` (inclusive total) with a
-// cached-read and cache-write subsets, and `completion_tokens` (inclusive
+// `cached_tokens` subset, and `completion_tokens` (inclusive total) with
-// total) with a `reasoning_tokens` subset. We pass the inclusive totals
+// a `reasoning_tokens` subset. We pass the inclusive totals through and
-// through and derive the non-cached breakdown so the `LLM.Usage` contract is
+// derive the non-cached breakdown so the `LLM.Usage` contract is
 // satisfied on both sides.
 const mapUsage = (usage: OpenAIChatEvent["usage"]): Usage | undefined => {
  if (!usage) return undefined
  const cached = usage.prompt_tokens_details?.cached_tokens
  const cacheWrite = usage.prompt_tokens_details?.cache_write_tokens
  const reasoning = usage.completion_tokens_details?.reasoning_tokens
-  const nonCached = ProviderShared.subtractTokens(usage.prompt_tokens, ProviderShared.sumTokens(cached, cacheWrite))
+  const nonCached = ProviderShared.subtractTokens(usage.prompt_tokens, cached)
  return new Usage({
    inputTokens: usage.prompt_tokens,
    outputTokens: usage.completion_tokens,
    nonCachedInputTokens: nonCached,
    cacheReadInputTokens: cached,
    cacheWriteInputTokens: cacheWrite,
    reasoningTokens: reasoning,
    totalTokens: ProviderShared.totalTokens(usage.prompt_tokens, usage.completion_tokens, usage.total_tokens),
    providerMetadata: { openai: usage },
@@ -545,22 +532,10 @@ const reasoningMetadata = (field: ParserState["reasoningField"], details?: Reado
 const step = (state: ParserState, event: OpenAIChatEvent) =>
  Effect.gen(function* () {
    if (event.error)
      return yield* new LLMError({
        module: ADAPTER,
        method: "stream",
        reason: classifyProviderFailure({
          message: event.error.message,
          code: event.error.code === undefined || event.error.code === null ? undefined : String(event.error.code),
          status: typeof event.error.code === "number" ? event.error.code : undefined,
        }),
      })
    const events: LLMEvent[] = []
    const usage = mapUsage(event.usage) ?? state.usage
-    const choice = event.choices?.[0]
+    const choice = event.choices[0]
-    const finishReason = choice?.finish_reason
+    const finishReason = choice?.finish_reason ? mapFinishReason(choice.finish_reason) : state.finishReason
      ? { normalized: mapFinishReason(choice.finish_reason), raw: choice.native_finish_reason ?? choice.finish_reason }
      : state.finishReason
    const delta = choice?.delta
    const toolDeltas = delta?.tool_calls ?? []
    let tools = state.tools
@@ -652,13 +627,7 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
 const finishEvents = (state: ParserState): ReadonlyArray<LLMEvent> => {
  const events: LLMEvent[] = []
  const hasToolCalls = state.toolCallEvents.length > 0
-  const reason = state.finishReason
+  const reason = state.finishReason === "stop" && hasToolCalls ? "tool-calls" : state.finishReason
    ? {
        ...state.finishReason,
        normalized:
          state.finishReason.normalized === "stop" && hasToolCalls ? "tool-calls" : state.finishReason.normalized,
      }
    : undefined
  const metadata = reasoningMetadata(
    state.reasoningField,
    state.reasoningDetailsObserved ? state.reasoningDetails : undefined,
@@ -1,22 +1,23 @@
 import { Route, type RouteRoutedModelInput } from "../route/client"
 import { Endpoint } from "../route/endpoint"
-import { OpenResponses } from "./open-responses"
+import { OpenAIResponses } from "./openai-responses"
 const ADAPTER = "openai-compatible-responses"
 export type OpenAICompatibleResponsesModelInput = RouteRoutedModelInput
 /**
- * Deployment adapter for providers that expose an Open Responses-compatible
+ * Route for providers that expose an OpenAI Responses-compatible `/responses`
- * `/responses` endpoint. Provider helpers configure identity, endpoint, and
+ * endpoint. Provider helpers configure identity, endpoint, and auth before
- * auth while the semantic protocol remains provider-neutral.
+ * model selection while this route reuses the OpenAI Responses protocol.
 */
 export const route = Route.make({
  id: ADAPTER,
-  providerMetadataKey: "openresponses",
+  providerMetadataKey: "openai",
-  protocol: OpenResponses.protocol,
+  protocol: OpenAIResponses.protocol,
-  endpoint: Endpoint.path(OpenResponses.PATH),
+  endpoint: Endpoint.path(OpenAIResponses.PATH),
-  transport: OpenResponses.httpTransport,
+  transport: OpenAIResponses.httpTransport,
  defaults: { providerOptions: { openai: { store: false } } },
 })
 export * as OpenAICompatibleResponses from "./openai-compatible-responses"
@@ -1,5 +1,4 @@
 import { Buffer } from "node:buffer"
 import { Tool } from "@opencode-ai/schema/tool"
 import { Effect, Schema, Stream } from "effect"
 import * as Sse from "effect/unstable/encoding/Sse"
 import { Headers, HttpClientRequest } from "effect/unstable/http"
@@ -10,6 +9,7 @@ import {
  type ContentPart,
  type LLMRequest,
  type MediaPart,
  type ToolFileContent,
  type TextPart,
  type ToolResultPart,
 } from "../schema"
@@ -206,7 +206,7 @@ export const validateMedia = Effect.fn("ProviderShared.validateMedia")(function*
  return { mime, base64, dataUrl: `data:${mime};base64,${base64}`, bytes } satisfies ValidatedMedia
 })
-export const validateToolFile = (route: string, part: Tool.FileContent, supportedMimes: ReadonlySet<string>) =>
+export const validateToolFile = (route: string, part: ToolFileContent, supportedMimes: ReadonlySet<string>) =>
  validateMedia(route, { type: "media", mediaType: part.mime, data: part.uri, filename: part.name }, supportedMimes)
 export const trimBaseUrl = (value: string) => value.replace(/\/+$/, "")
@@ -1,4 +1,4 @@
-import { LLMEvent, type FinishReasonDetails, type ProviderMetadata, type Usage } from "../../schema"
+import { LLMEvent, type FinishReason, type ProviderMetadata, type Usage } from "../../schema"
 export interface State {
  readonly stepStarted: boolean
@@ -14,17 +14,14 @@ export const stepStart = (state: State, events: LLMEvent[]): State => {
  return { ...state, stepStarted: true }
 }
 export const textStart = (state: State, events: LLMEvent[], id: string, providerMetadata?: ProviderMetadata): State => {
  if (state.text.has(id)) return state
  const stepped = stepStart(state, events)
  events.push(LLMEvent.textStart({ id, providerMetadata }))
  return { ...stepped, text: new Set([...stepped.text, id]) }
 }
 export const textDelta = (state: State, events: LLMEvent[], id: string, text: string): State => {
-  const started = textStart(state, events, id)
+  const stepped = stepStart(state, events)
-  events.push(LLMEvent.textDelta({ id, text }))
+  if (stepped.text.has(id)) {
-  return started
+    events.push(LLMEvent.textDelta({ id, text }))
    return stepped
  }
  events.push(LLMEvent.textStart({ id }), LLMEvent.textDelta({ id, text }))
  return { ...stepped, text: new Set([...stepped.text, id]) }
 }
 export const reasoningStart = (
@@ -84,7 +81,7 @@ export const finish = (
  state: State,
  events: LLMEvent[],
  input: {
-    readonly reason: FinishReasonDetails
+    readonly reason: FinishReason
    readonly usage?: Usage
    readonly providerMetadata?: ProviderMetadata
  },
@@ -1,65 +0,0 @@
 import { Schema } from "effect"
 import { TextVerbosity, type LLMRequest } from "../../schema"
 export const ResponseIncludables = [
  "file_search_call.results",
  "web_search_call.results",
  "web_search_call.action.sources",
  "message.input_image.image_url",
  "computer_call_output.output.image_url",
  "code_interpreter_call.outputs",
  "reasoning.encrypted_content",
  "message.output_text.logprobs",
 ] as const
 export type ResponseIncludable = (typeof ResponseIncludables)[number]
 export const ServiceTiers = ["auto", "default", "flex", "priority"] as const
 export type ServiceTier = (typeof ServiceTiers)[number]
 const TEXT_VERBOSITY = new Set<string>(["low", "medium", "high"])
 const INCLUDABLES = new Set<string>(ResponseIncludables)
 const SERVICE_TIERS = new Set<string>(ServiceTiers)
 const isTextVerbosity = (value: unknown): value is Schema.Schema.Type<typeof TextVerbosity> =>
  typeof value === "string" && TEXT_VERBOSITY.has(value)
 const isServiceTier = (value: unknown): value is ServiceTier => typeof value === "string" && SERVICE_TIERS.has(value)
 export const ReasoningEffort = Schema.String
 export const TextVerbositySchema = TextVerbosity
 export const ResponseIncludableSchema = Schema.Literals(ResponseIncludables)
 export const ServiceTierSchema = Schema.Literals(ServiceTiers)
 export interface Resolved {
  readonly instructions?: string
  readonly store?: boolean
  readonly promptCacheKey?: string
  readonly reasoningEffort?: string
  readonly reasoningSummary?: "auto" | "concise" | "detailed"
  readonly include?: ReadonlyArray<ResponseIncludable>
  readonly textVerbosity?: Schema.Schema.Type<typeof TextVerbosity>
  readonly serviceTier?: ServiceTier
 }
 export const resolve = (request: LLMRequest): Resolved => {
  const input = request.providerOptions?.[request.model.route.providerMetadataKey ?? "openresponses"]
  const include = Array.isArray(input?.include)
    ? input.include.filter((entry): entry is ResponseIncludable => INCLUDABLES.has(entry))
    : []
  const reasoningSummary = input?.reasoningSummary
  return {
    instructions: typeof input?.instructions === "string" ? input.instructions : undefined,
    store: typeof input?.store === "boolean" ? input.store : undefined,
    promptCacheKey: typeof input?.promptCacheKey === "string" ? input.promptCacheKey : undefined,
    reasoningEffort: typeof input?.reasoningEffort === "string" ? input.reasoningEffort : undefined,
    reasoningSummary:
      reasoningSummary === "auto" || reasoningSummary === "concise" || reasoningSummary === "detailed"
        ? reasoningSummary
        : undefined,
    include: include.length > 0 ? include : undefined,
    textVerbosity: isTextVerbosity(input?.textVerbosity) ? input.textVerbosity : undefined,
    serviceTier: isServiceTier(input?.serviceTier) ? input.serviceTier : undefined,
  }
 }
 export * as OpenResponsesOptions from "./open-responses-options"
@@ -1,23 +1,85 @@
-import { ReasoningEfforts } from "../../schema"
+import { Schema } from "effect"
-import { OpenResponsesOptions } from "./open-responses-options"
+import type { LLMRequest, TextVerbosity as TextVerbosityValue } from "../../schema"
 import { ReasoningEfforts, TextVerbosity } from "../../schema"
 export const OpenAIReasoningEfforts = ReasoningEfforts
 export type OpenAIReasoningEffort = string
 // Mirrors OpenAI's `ResponseIncludable` union from the official SDK. Keep this
 // in lockstep with `openai-node/src/resources/responses/responses.ts`.
-export const OpenAIResponseIncludables = OpenResponsesOptions.ResponseIncludables
+export const OpenAIResponseIncludables = [
-export type OpenAIResponseIncludable = OpenResponsesOptions.ResponseIncludable
+  "file_search_call.results",
-export const OpenAIServiceTiers = OpenResponsesOptions.ServiceTiers
+  "web_search_call.results",
-export type OpenAIServiceTier = OpenResponsesOptions.ServiceTier
+  "web_search_call.action.sources",
  "message.input_image.image_url",
  "computer_call_output.output.image_url",
  "code_interpreter_call.outputs",
  "reasoning.encrypted_content",
  "message.output_text.logprobs",
 ] as const
 export type OpenAIResponseIncludable = (typeof OpenAIResponseIncludables)[number]
 export const OpenAIServiceTiers = ["auto", "default", "flex", "priority"] as const
 export type OpenAIServiceTier = (typeof OpenAIServiceTiers)[number]
-export const OpenAIReasoningEffort = OpenResponsesOptions.ReasoningEffort
+const TEXT_VERBOSITY = new Set<string>(["low", "medium", "high"])
-export const OpenAITextVerbosity = OpenResponsesOptions.TextVerbositySchema
+const INCLUDABLES = new Set<string>(OpenAIResponseIncludables)
-export const OpenAIResponseIncludable = OpenResponsesOptions.ResponseIncludableSchema
+const SERVICE_TIERS = new Set<string>(OpenAIServiceTiers)
-export const OpenAIServiceTier = OpenResponsesOptions.ServiceTierSchema
+
 export const OpenAIReasoningEffort = Schema.String
 export const OpenAITextVerbosity = TextVerbosity
 export const OpenAIResponseIncludable = Schema.Literals(OpenAIResponseIncludables)
 export const OpenAIServiceTier = Schema.Literals(OpenAIServiceTiers)
 export const isReasoningEffort = (effort: unknown): effort is OpenAIReasoningEffort => typeof effort === "string"
-export const resolve = OpenResponsesOptions.resolve
+const isTextVerbosity = (value: unknown): value is TextVerbosityValue =>
  typeof value === "string" && TEXT_VERBOSITY.has(value)
 const options = (request: LLMRequest) => request.providerOptions?.openai
 export const store = (request: LLMRequest): boolean | undefined => {
  const value = options(request)?.store
  return typeof value === "boolean" ? value : undefined
 }
 export const reasoningEffort = (request: LLMRequest): string | undefined => {
  const value = options(request)?.reasoningEffort
  return typeof value === "string" ? value : undefined
 }
 export const reasoningSummary = (request: LLMRequest): "auto" | undefined =>
  options(request)?.reasoningSummary === "auto" ? "auto" : undefined
 // Resolve the OpenAI Responses `include` field. Filters out unknown
 // includable values defensively so a typo in upstream config drops the
 // invalid entry instead of poisoning the wire body. An empty array (either
 // passed directly or produced by filtering) is treated as "no include" and
 // returns undefined so the request body omits the field entirely.
 export const include = (request: LLMRequest): ReadonlyArray<OpenAIResponseIncludable> | undefined => {
  const value = options(request)?.include
  if (!Array.isArray(value)) return undefined
  const filtered = value.filter((entry): entry is OpenAIResponseIncludable => INCLUDABLES.has(entry))
  return filtered.length > 0 ? filtered : undefined
 }
 export const promptCacheKey = (request: LLMRequest) => {
  const value = options(request)?.promptCacheKey
  return typeof value === "string" ? value : undefined
 }
 export const textVerbosity = (request: LLMRequest) => {
  const value = options(request)?.textVerbosity
  return isTextVerbosity(value) ? value : undefined
 }
 export const serviceTier = (request: LLMRequest) => {
  const value = options(request)?.serviceTier
  return typeof value === "string" && SERVICE_TIERS.has(value) ? (value as OpenAIServiceTier) : undefined
 }
 export const instructions = (request: LLMRequest) => {
  const value = options(request)?.instructions
  return typeof value === "string" ? value : undefined
 }
 export * as OpenAIOptions from "./openai-options"
@@ -63,8 +63,6 @@ const openAI = (schema: JsonSchema): JsonSchema => {
  return isRecord(normalized) ? normalized : { type: "object" }
 }
 const responses = openAI
 const gemini = (schema: JsonSchema): JsonSchema => GeminiToolSchema.convert(schema) ?? {}
 const modelCompatibility = (
@@ -85,5 +83,4 @@ export const ToolSchemaProjection = {
  modelCompatibility,
  moonshot,
  openAI,
  responses,
 } as const
@@ -135,7 +135,7 @@ export function classifyProviderFailure(input: ProviderFailure): LLMError["reaso
      rateLimit: input.rateLimit,
    })
  }
-  if (input.status === 408 || input.status === 409 || (input.status !== undefined && input.status >= 500))
+  if (input.status !== undefined && input.status >= 500)
    return new ProviderInternalReason({
      ...common,
      status: input.status,
@@ -145,6 +145,7 @@ export function classifyProviderFailure(input: ProviderFailure): LLMError["reaso
  if (
    input.status === 400 ||
    input.status === 404 ||
    input.status === 409 ||
    input.status === 413 ||
    input.status === 422
  )
@@ -5,17 +5,12 @@ import type { ProviderAuthOption } from "../route/auth-options"
 import type { RouteDefaultsInput } from "../route/client"
 import { ProviderID, type ModelID } from "../schema"
 export type AnthropicOptionsInput = AnthropicMessages.OptionsInput
 export type AnthropicProviderOptionsInput = AnthropicMessages.ProviderOptionsInput
 export type AnthropicThinkingInput = AnthropicMessages.ThinkingInput
 export const id = ProviderID.make("anthropic-compatible")
 export type Config = RouteDefaultsInput &
  ProviderAuthOption<"optional"> & {
    readonly provider?: string
    readonly baseURL: string
    readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
  }
 export type Settings = ProviderPackage.Settings &
@@ -25,7 +20,6 @@ export type Settings = ProviderPackage.Settings &
  ) & {
    readonly baseURL: string
    readonly provider?: string
    readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
  }
 export const routes = [AnthropicMessages.route]
@@ -67,7 +61,6 @@ export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, se
    http: settings.body === undefined ? undefined : { body: { ...settings.body } },
    limits: settings.limits,
    provider: settings.provider,
    providerOptions: settings.providerOptions,
  }).model(modelID)
 }
@@ -6,19 +6,11 @@ import { ProviderID, type ModelID } from "../schema"
 import { AnthropicMessages } from "../protocols/anthropic-messages"
 import { AnthropicCompatible } from "./anthropic-compatible"
 export type AnthropicOptionsInput = AnthropicMessages.OptionsInput
 export type AnthropicProviderOptionsInput = AnthropicMessages.ProviderOptionsInput
 export type AnthropicThinkingInput = AnthropicMessages.ThinkingInput
 export const id = ProviderID.make("anthropic")
 export const routes = [AnthropicMessages.route]
-export type Config = RouteDefaultsInput &
+export type Config = RouteDefaultsInput & ProviderAuthOption<"optional"> & { readonly baseURL?: string }
  ProviderAuthOption<"optional"> & {
    readonly baseURL?: string
    readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
  }
 export type Settings = ProviderPackage.Settings &
  (
@@ -26,7 +18,6 @@ export type Settings = ProviderPackage.Settings &
    | { readonly apiKey?: never; readonly authToken?: string }
  ) & {
    readonly baseURL?: string
    readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
  }
 const auth = (options: ProviderAuthOption<"optional">) => {
@@ -61,6 +52,5 @@ export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, se
    headers: settings.headers === undefined ? undefined : { ...settings.headers },
    http: settings.body === undefined ? undefined : { body: { ...settings.body } },
    limits: settings.limits,
    providerOptions: settings.providerOptions,
  }).model(modelID)
 }
@@ -6,13 +6,9 @@ import { Route, type RouteDefaultsInput } from "../route/client"
 import { Endpoint } from "../route/endpoint"
 import { Framing } from "../route/framing"
 import { Protocol } from "../route/protocol"
-import { ProviderID, type ModelID } from "../schema"
+import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
 import { GoogleVertexShared } from "./google-vertex-shared"
 export type AnthropicOptionsInput = AnthropicMessages.OptionsInput
 export type AnthropicProviderOptionsInput = AnthropicMessages.ProviderOptionsInput
 export type AnthropicThinkingInput = AnthropicMessages.ThinkingInput
 const VERSION = "vertex-2023-10-16" as const
 // models.dev uses this provider id even though the API contract is Anthropic Messages.
@@ -23,7 +19,6 @@ export type Config = RouteDefaultsInput &
    readonly baseURL?: string
    readonly location?: string
    readonly project?: string
    readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
  }
 export interface Settings extends ProviderPackage.Settings {
@@ -32,7 +27,7 @@ export interface Settings extends ProviderPackage.Settings {
  readonly baseURL?: string
  readonly location?: string
  readonly project?: string
-  readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
+  readonly providerOptions?: ProviderOptions
 }
 const route = Route.make({
@@ -25,7 +25,6 @@ export interface Settings extends ProviderPackage.Settings {
 const route = OpenAICompatibleResponses.route.with({
  id: "google-vertex-responses",
  provider: id,
  providerOptions: { openresponses: { store: false } },
 })
 export const routes = [route]
@@ -4,12 +4,9 @@ import { Auth } from "../route/auth"
 import { Route, type RouteDefaultsInput } from "../route/client"
 import { Endpoint } from "../route/endpoint"
 import { Framing } from "../route/framing"
-import { ProviderID, type ModelID } from "../schema"
+import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
 import { GoogleVertexShared } from "./google-vertex-shared"
 export type GeminiOptionsInput = Gemini.OptionsInput
 export type GeminiProviderOptionsInput = Gemini.ProviderOptionsInput
 export const id = ProviderID.make("google-vertex")
 export type Config = RouteDefaultsInput &
@@ -17,7 +14,6 @@ export type Config = RouteDefaultsInput &
    readonly baseURL?: string
    readonly location?: string
    readonly project?: string
    readonly providerOptions?: Gemini.ProviderOptionsInput
  }
 export type Settings = ProviderPackage.Settings &
@@ -28,7 +24,7 @@ export type Settings = ProviderPackage.Settings &
    readonly baseURL?: string
    readonly location?: string
    readonly project?: string
-    readonly providerOptions?: Gemini.ProviderOptionsInput
+    readonly providerOptions?: ProviderOptions
  }
 const route = Route.make({
@@ -2,13 +2,11 @@ import type { RouteDefaultsInput } from "../route/client"
 import { Auth } from "../route/auth"
 import type { ProviderAuthOption } from "../route/auth-options"
 import type { ProviderPackage } from "../provider-package"
-import { HttpOptions, ProviderID, mergeHttpOptions, type ModelID } from "../schema"
+import { HttpOptions, ProviderID, mergeHttpOptions, type ModelID, type ProviderOptions } from "../schema"
 import { Gemini } from "../protocols/gemini"
 import { GoogleImages } from "../protocols/google-images"
 export type { GoogleImageOptions } from "../protocols/google-images"
 export type GeminiOptionsInput = Gemini.OptionsInput
 export type GeminiProviderOptionsInput = Gemini.ProviderOptionsInput
 export const id = ProviderID.make("google")
@@ -17,13 +15,12 @@ export const routes = [Gemini.route]
 export type Config = RouteDefaultsInput &
  ProviderAuthOption<"optional"> & {
    readonly baseURL?: string
    readonly providerOptions?: Gemini.ProviderOptionsInput
  }
 export interface Settings extends ProviderPackage.Settings {
  readonly apiKey?: string
  readonly baseURL?: string
-  readonly providerOptions?: Gemini.ProviderOptionsInput
+  readonly providerOptions?: ProviderOptions
 }
 const auth = (options: ProviderAuthOption<"optional">) => {
@@ -1,20 +0,0 @@
 import type { ResponseIncludable, ServiceTier } from "../protocols/utils/open-responses-options"
 import type { ProviderOptions, ReasoningEffort, TextVerbosity } from "../schema"
 export interface OpenResponsesOptionsInput {
  readonly [key: string]: unknown
  readonly instructions?: string
  readonly store?: boolean
  readonly promptCacheKey?: string
  readonly reasoningEffort?: ReasoningEffort
  readonly reasoningSummary?: "auto" | "concise" | "detailed"
  readonly include?: ReadonlyArray<ResponseIncludable>
  readonly textVerbosity?: TextVerbosity
  readonly serviceTier?: ServiceTier
 }
 export type OpenResponsesProviderOptionsInput = ProviderOptions & {
  readonly openresponses?: OpenResponsesOptionsInput
 }
 export * as OpenResponsesProviderOptions from "./open-responses-options"
@@ -3,9 +3,7 @@ import { OpenAICompatibleResponses } from "../protocols/openai-compatible-respon
 import { AuthOptions, type ProviderAuthOption } from "../route/auth-options"
 import type { RouteDefaultsInput } from "../route/client"
 import { ProviderID, type ModelID } from "../schema"
-import type { OpenResponsesProviderOptionsInput } from "./open-responses-options"
+import type { OpenAIProviderOptionsInput } from "./openai-options"
 export type { OpenResponsesOptionsInput, OpenResponsesProviderOptionsInput } from "./open-responses-options"
 export const id = ProviderID.make("openai-compatible")
@@ -13,14 +11,13 @@ export type Config = RouteDefaultsInput &
  ProviderAuthOption<"optional"> & {
    readonly provider?: string
    readonly baseURL: string
    readonly providerOptions?: OpenResponsesProviderOptionsInput
  }
 export interface Settings extends ProviderPackage.Settings {
  readonly apiKey?: string
  readonly baseURL: string
  readonly provider?: string
-  readonly providerOptions?: OpenResponsesProviderOptionsInput
+  readonly providerOptions?: OpenAIProviderOptionsInput
 }
 export const routes = [OpenAICompatibleResponses.route]
@@ -1,10 +1,22 @@
-import type { ProviderOptions } from "../schema"
+import type { ProviderOptions, ReasoningEffort, TextVerbosity } from "../schema"
 import { mergeProviderOptions } from "../schema"
-import type { OpenResponsesOptionsInput } from "./open-responses-options"
+import type { OpenAIResponseIncludable, OpenAIServiceTier } from "../protocols/utils/openai-options"
 export type { OpenAIResponseIncludable, OpenAIServiceTier } from "../protocols/utils/openai-options"
-export type OpenAIOptionsInput = OpenResponsesOptionsInput
+export interface OpenAIOptionsInput {
  readonly [key: string]: unknown
  readonly store?: boolean
  readonly promptCacheKey?: string
  readonly reasoningEffort?: ReasoningEffort
  readonly reasoningSummary?: "auto"
  // OpenAI Responses `include` wire field. Mirrors the official SDK's
  // `ResponseIncludable[]` union exactly so AI SDK callers and direct
  // native-SDK callers share one shape and no translation is required.
  readonly include?: ReadonlyArray<OpenAIResponseIncludable>
  readonly textVerbosity?: TextVerbosity
  readonly serviceTier?: OpenAIServiceTier
 }
 export type OpenAIProviderOptionsInput = ProviderOptions & {
  readonly openai?: OpenAIOptionsInput
@@ -12,8 +12,7 @@ import type { LLMError, LLMEvent, LLMRequest, ProtocolID } from "../schema"
 * Examples:
 *
 * - `OpenAIChat.protocol` — chat completions style
- * - `OpenResponses.protocol` — provider-neutral Responses API baseline
+ * - `OpenAIResponses.protocol` — responses API
 * - `OpenAIResponses.protocol` — OpenAI extensions to that baseline
 * - `AnthropicMessages.protocol` — messages API with content blocks
 * - `Gemini.protocol` — generateContent
 * - `BedrockConverse.protocol` — Converse with binary event-stream framing
@@ -1,5 +1,4 @@
 import { Schema } from "effect"
 import { Tool } from "@opencode-ai/schema/tool"
 import { ModelID, ProviderID, ProviderMetadata, RouteID } from "./ids"
 export const ProviderFailureClassification = Schema.Literal("context-overflow")
@@ -153,4 +152,8 @@ export class LLMError extends Schema.TaggedErrorClass<LLMError>()("LLM.Error", {
 * Anything thrown or yielded by a handler that is not a `ToolFailure` is
 * treated as a defect and fails the stream.
 */
-export class ToolFailure extends Tool.Error {}
+export class ToolFailure extends Schema.TaggedErrorClass<ToolFailure>()("LLM.ToolFailure", {
  message: Schema.String,
  error: Schema.optional(Schema.Defect()),
  metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
 }) {}
@@ -40,9 +40,9 @@ import { ProviderFailureClassification } from "./errors"
 * - Anthropic and Bedrock report the input breakdown natively: Anthropic's
 *   `input_tokens` and Bedrock's `inputTokens` are non-cached only. Their
 *   mappers sum the breakdown to derive the inclusive `inputTokens`.
- *   Anthropic's `outputTokens` includes extended thinking. Newer responses
+ *   Anthropic does *not* break extended-thinking out of `output_tokens`, so
- *   expose that subset as `output_tokens_details.thinking_tokens`, which maps
+ *   `reasoningTokens` is `undefined` and `outputTokens` carries the
- *   to `reasoningTokens`; older responses leave it undefined.
+ *   combined total — a documented limitation of the Anthropic API.
 *
 * `providerMetadata` always carries the provider's raw usage payload —
 * keyed by provider name (`{ openai: ... }`, `{ anthropic: ... }`, etc.)
@@ -191,16 +191,10 @@ export const ToolError = Schema.Struct({
 }).annotate({ identifier: "LLM.Event.ToolError" })
 export type ToolError = Schema.Schema.Type<typeof ToolError>
 export const FinishReasonDetails = Schema.Struct({
  normalized: FinishReason,
  raw: Schema.optional(Schema.String),
 }).annotate({ identifier: "LLM.FinishReasonDetails" })
 export type FinishReasonDetails = Schema.Schema.Type<typeof FinishReasonDetails>
 export const StepFinish = Schema.Struct({
  type: Schema.tag("step-finish"),
  index: Schema.Number,
-  reason: FinishReasonDetails,
+  reason: FinishReason,
  usage: Schema.optional(Usage),
  providerMetadata: Schema.optional(ProviderMetadata),
 }).annotate({ identifier: "LLM.Event.StepFinish" })
@@ -208,7 +202,7 @@ export type StepFinish = Schema.Schema.Type<typeof StepFinish>
 export const Finish = Schema.Struct({
  type: Schema.tag("finish"),
-  reason: FinishReasonDetails,
+  reason: FinishReason,
  usage: Schema.optional(Usage),
  providerMetadata: Schema.optional(ProviderMetadata),
 }).annotate({ identifier: "LLM.Event.Finish" })
@@ -371,7 +365,7 @@ interface ResponseState {
  readonly events: ReadonlyArray<LLMEvent>
  readonly message: Message
  readonly usage?: Usage
-  readonly finishReason?: FinishReasonDetails
+  readonly finishReason?: FinishReason
  readonly textParts: Readonly<Record<string, ContentAssembly>>
  readonly reasoningParts: Readonly<Record<string, ContentAssembly>>
  readonly toolInputs: Readonly<Record<string, ToolInputAssembly>>
@@ -399,7 +393,7 @@ const appendEvent = (state: ResponseState, event: LLMEvent): ResponseState => {
    return {
      ...state,
      events,
-      finishReason: state.finishReason ?? { normalized: "error" },
+      finishReason: state.finishReason ?? "error",
    }
  }
  return {
@@ -586,7 +580,7 @@ export class LLMResponse extends Schema.Class<LLMResponse>("LLM.Response")({
  message: Message,
  events: Schema.Array(LLMEvent),
  usage: Schema.optional(Usage),
-  finishReason: FinishReasonDetails,
+  finishReason: FinishReason,
 }) {
  /** Concatenated assistant text assembled from streamed `text-delta` events. */
  get text() {
@@ -1,5 +1,5 @@
 import { Schema } from "effect"
-import { Tool } from "@opencode-ai/schema/tool"
+import { ToolContent, ToolFileContent, ToolTextContent } from "@opencode-ai/schema/llm"
 import { JsonSchema, MessageRole, ProviderMetadata } from "./ids"
 import { CacheHint, CachePolicy, GenerationOptions, HttpOptions, ModelSchema, ProviderOptions } from "./options"
 import { isRecord } from "../utils/record"
@@ -40,6 +40,8 @@ export const MediaPart = Schema.Struct({
 }).annotate({ identifier: "LLM.Content.Media" })
 export type MediaPart = Schema.Schema.Type<typeof MediaPart>
 export { ToolContent, ToolFileContent, ToolTextContent }
 const isToolResultValue = (value: unknown): value is ToolResultValue =>
  isRecord(value) &&
  (value.type === "text" || value.type === "json" || value.type === "error" || value.type === "content") &&
@@ -61,7 +63,7 @@ export const ToolResultValue = Object.assign(
    }),
    Schema.Struct({
      type: Schema.Literal("content"),
-      value: Schema.Array(Tool.Content),
+      value: Schema.Array(ToolContent),
    }),
  ]).annotate({ identifier: "LLM.ToolResult" }),
  {
@@ -77,16 +79,16 @@ export type ToolResultValue = Schema.Schema.Type<typeof ToolResultValue>
 export interface ToolOutput {
  readonly structured: unknown
-  readonly content: ReadonlyArray<Tool.Content>
+  readonly content: ReadonlyArray<ToolContent>
 }
 export const ToolOutput = Object.assign(
  Schema.Struct({
    structured: Schema.Unknown,
-    content: Schema.Array(Tool.Content),
+    content: Schema.Array(ToolContent),
  }).annotate({ identifier: "LLM.ToolOutput" }),
  {
-    make: (structured: unknown, content: ReadonlyArray<Tool.Content> = []): ToolOutput => ({ structured, content }),
+    make: (structured: unknown, content: ReadonlyArray<ToolContent> = []): ToolOutput => ({ structured, content }),
    fromResultValue: (result: ToolResultValue): ToolOutput | undefined => {
      switch (result.type) {
        case "json":
@@ -259,6 +261,13 @@ export namespace ToolChoice {
  }
 }
 export const ResponseFormat = Schema.Union([
  Schema.Struct({ type: Schema.Literal("text") }),
  Schema.Struct({ type: Schema.Literal("json"), schema: JsonSchema }),
  Schema.Struct({ type: Schema.Literal("tool"), tool: ToolDefinition }),
 ]).pipe(Schema.toTaggedUnion("type"))
 export type ResponseFormat = Schema.Schema.Type<typeof ResponseFormat>
 export class LLMRequest extends Schema.Class<LLMRequest>("LLM.Request")({
  id: Schema.optional(Schema.String),
  model: ModelSchema,
@@ -269,6 +278,7 @@ export class LLMRequest extends Schema.Class<LLMRequest>("LLM.Request")({
  generation: Schema.optional(GenerationOptions),
  providerOptions: Schema.optional(ProviderOptions),
  http: Schema.optional(HttpOptions),
  responseFormat: Schema.optional(ResponseFormat),
  cache: Schema.optional(CachePolicy),
  metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
 }) {}
@@ -286,6 +296,7 @@ export namespace LLMRequest {
    generation: request.generation,
    providerOptions: request.providerOptions,
    http: request.http,
    responseFormat: request.responseFormat,
    cache: request.cache,
    metadata: request.metadata,
  })
@@ -251,11 +251,11 @@ export class CacheHint extends Schema.Class<CacheHint>("LLM.CacheHint")({
 // Auto-placement policy for prompt caching. The protocol-neutral lowering step
 // reads this and injects `CacheHint`s at the configured boundaries; the
 // per-protocol body builders then translate those hints into wire markers as
-// usual. `"auto"` is the recommended default for agent loops — it places
+// usual. `"auto"` is the recommended default for agent loops — it places one
-// breakpoints at the last tool definition, the first and last distinct system
+// breakpoint at the last tool definition, one at the last system part, and one
-// parts, and the conversation tail. The rolling message breakpoint keeps a
+// at the latest user message. The combination of provider invalidation
-// prior cache entry within Anthropic/Bedrock's 20-block lookback during long
+// hierarchy (tools → system → messages) and Anthropic/Bedrock's 20-block
-// tool loops.
+// lookback means three trailing breakpoints reliably cover the static prefix.
 //
 // Pass `"none"` to opt out entirely (the legacy behavior). Pass the granular
 // object form to override individual choices.
@@ -1,157 +0,0 @@
 export * as TestLLM from "./testing"
 import { LLMClient, type Interface as LLMClientShape } from "./route/client"
 import {
  LLMEvent,
  LLMResponse,
  type FinishReasonDetails,
  type LLMError,
  type LLMRequest,
  type UsageInput,
 } from "./schema"
 import { Context, Deferred, Effect, Latch, Layer, Queue, Scope, Stream } from "effect"
 export type Response = readonly LLMEvent[] | Stream.Stream<LLMEvent, LLMError>
 export type Gate = Readonly<{ started: Effect.Effect<void>; release: Effect.Effect<void> }>
 export interface Interface {
  readonly requests: LLMRequest[]
  readonly push: (...responses: readonly Response[]) => Effect.Effect<void>
  readonly always: (response: Response) => Effect.Effect<void>
  readonly wait: (count: number) => Effect.Effect<void>
  readonly gate: Effect.Effect<Gate, never, Scope.Scope>
  readonly client: LLMClientShape
 }
 export interface LayerOptions {
  readonly transformRequest?: (request: LLMRequest) => LLMRequest
  /** Used after the one-shot response queue is exhausted. Omit to defect on unexpected requests. */
  readonly fallback?: Response
 }
 export class Service extends Context.Service<Service, Interface>()("@opencode/ai/TestLLM") {}
 export const complete = (
  options: { readonly reason: FinishReasonDetails; readonly usage?: UsageInput },
  ...events: readonly LLMEvent[]
 ) => [
  LLMEvent.stepStart({ index: 0 }),
  ...events,
  LLMEvent.stepFinish({ index: 0, reason: options.reason, usage: options.usage }),
  LLMEvent.finish({ reason: options.reason }),
 ]
 export const stop = (...events: readonly LLMEvent[]) => complete({ reason: { normalized: "stop" } }, ...events)
 export const toolCalls = (...events: readonly LLMEvent[]) =>
  complete({ reason: { normalized: "tool-calls" } }, ...events)
 const textEvents = (value: string, id: string) => [
  LLMEvent.textStart({ id }),
  LLMEvent.textDelta({ id, text: value }),
  LLMEvent.textEnd({ id }),
 ]
 export const text = (value: string, id: string) => stop(...textEvents(value, id))
 export const textWithUsage = (value: string, id: string, inputTokens: number) =>
  complete(
    { reason: { normalized: "stop" }, usage: { inputTokens, nonCachedInputTokens: inputTokens } },
    ...textEvents(value, id),
  )
 export const tool = (id: string, name: string, input: unknown) => toolCalls(LLMEvent.toolCall({ id, name, input }))
 export const failAfter = (error: LLMError, ...events: readonly LLMEvent[]) =>
  Stream.fromIterable(events).pipe(Stream.concat(Stream.fail(error)))
 export const hangAfter = (...events: readonly LLMEvent[]) => Stream.concat(Stream.fromIterable(events), Stream.never)
 const toStream = (response: Response) => (Stream.isStream(response) ? response : Stream.fromIterable(response))
 export const layer = (options: LayerOptions = {}) =>
  Layer.effect(
    Service,
    Effect.gen(function* () {
      const requests: LLMRequest[] = []
      const responses: Response[] = []
      let started = Deferred.makeUnsafe<void>()
      let fallback = options.fallback
      let activeGate: { readonly started: Queue.Queue<void>; readonly release: Latch.Latch } | undefined
      const wait = (count: number): Effect.Effect<void> =>
        Effect.suspend(() =>
          requests.length >= count ? Effect.void : Deferred.await(started).pipe(Effect.andThen(wait(count))),
        )
      const stream = ((request: LLMRequest) => {
        requests.push(options.transformRequest?.(request) ?? request)
        const waiting = started
        started = Deferred.makeUnsafe()
        Deferred.doneUnsafe(waiting, Effect.void)
        const response = responses.shift() ?? fallback
        if (!response) return Stream.die(new Error(`TestLLM has no response for request ${requests.length}`))
        const streamed = toStream(response)
        const gate = activeGate
        if (!gate) return streamed
        return Stream.unwrap(
          Queue.offer(gate.started, undefined).pipe(Effect.andThen(gate.release.await), Effect.as(streamed)),
        )
      }) as LLMClientShape["stream"]
      const client = LLMClient.Service.of({
        prepare: () => Effect.die("TestLLM does not prepare provider-native requests"),
        stream,
        generate: (request) =>
          stream(request).pipe(
            Stream.runFold(LLMResponse.empty, LLMResponse.reduce),
            Effect.flatMap((state) => {
              const response = LLMResponse.complete(state)
              if (response) return Effect.succeed(response)
              return Effect.die("TestLLM response ended without a terminal finish event")
            }),
          ),
      })
      return Service.of({
        requests,
        push: (...input) =>
          Effect.sync(() => {
            responses.push(...input)
          }),
        always: (response) =>
          Effect.sync(() => {
            fallback = response
          }),
        wait,
        gate: Effect.gen(function* () {
          const gate = {
            started: yield* Effect.acquireRelease(Queue.unbounded<void>(), Queue.shutdown),
            release: yield* Latch.make(),
          }
          activeGate = gate
          const release = Effect.sync(() => {
            if (activeGate === gate) activeGate = undefined
          }).pipe(Effect.andThen(gate.release.open), Effect.asVoid)
          yield* Effect.addFinalizer(() => release)
          return {
            started: Queue.take(gate.started),
            release,
          }
        }),
        client,
      })
    }),
  )
 export const clientLayer = Layer.effect(
  LLMClient.Service,
  Effect.map(Service, (service) => service.client),
 )
 export const push = (...responses: readonly Response[]) => Service.use((service) => service.push(...responses))
 export const always = (response: Response) => Service.use((service) => service.always(response))
 export const wait = (count: number) => Service.use((service) => service.wait(count))
 export const gate = Service.use((service) => service.gate)
@@ -28,7 +28,7 @@ export const dispatch = (tools: Tools, call: ToolCallPart): Effect.Effect<Dispat
  return decodeAndExecute(tool, call).pipe(
    Effect.map((value) => result(call, value)),
-    Effect.catchTag("Tool.Error", (failure) =>
+    Effect.catchTag("LLM.ToolFailure", (failure) =>
      Effect.succeed(result(call, { type: "error", value: failure.message }, failure.error)),
    ),
  )
@@ -1,7 +1,7 @@
 import { Effect, JsonSchema, Schema } from "effect"
 import { Tool } from "@opencode-ai/schema/tool"
 import type {
  ToolCallPart,
  ToolContent,
  ToolDefinition as ToolDefinitionClass,
  ToolOutput as ToolOutputType,
 } from "./schema"
@@ -31,7 +31,7 @@ export interface ToolModelOutputInput<Parameters, Output> {
 export type ToolToModelOutput<Parameters extends ToolSchema<any>, Success extends ToolSchema<any>> = (
  input: ToolModelOutputInput<Schema.Schema.Type<Parameters>, Success["Encoded"]>,
-) => ReadonlyArray<Tool.Content>
+) => ReadonlyArray<ToolContent>
 /**
 * A type-safe LLM tool. Each tool bundles its own description, parameter
@@ -95,7 +95,7 @@ type DynamicToolConfig = {
  readonly jsonSchema: JsonSchema.JsonSchema
  readonly outputSchema?: JsonSchema.JsonSchema
  readonly execute?: (params: unknown, context?: ToolExecuteContext) => Effect.Effect<unknown, ToolFailure>
-  readonly toModelOutput?: (input: ToolModelOutputInput<unknown, unknown>) => ReadonlyArray<Tool.Content>
+  readonly toModelOutput?: (input: ToolModelOutputInput<unknown, unknown>) => ReadonlyArray<ToolContent>
  readonly toStructuredOutput?: (output: unknown) => unknown
 }
@@ -151,7 +151,7 @@ export function make(config: {
  readonly jsonSchema: JsonSchema.JsonSchema
  readonly outputSchema?: JsonSchema.JsonSchema
  readonly execute: (params: unknown, context?: ToolExecuteContext) => Effect.Effect<unknown, ToolFailure>
-  readonly toModelOutput?: (input: ToolModelOutputInput<unknown, unknown>) => ReadonlyArray<Tool.Content>
+  readonly toModelOutput?: (input: ToolModelOutputInput<unknown, unknown>) => ReadonlyArray<ToolContent>
  readonly toStructuredOutput?: (output: unknown) => unknown
 }): AnyExecutableTool
 export function make(config: {
@@ -159,7 +159,7 @@ export function make(config: {
  readonly jsonSchema: JsonSchema.JsonSchema
  readonly outputSchema?: JsonSchema.JsonSchema
  readonly execute?: undefined
-  readonly toModelOutput?: (input: ToolModelOutputInput<unknown, unknown>) => ReadonlyArray<Tool.Content>
+  readonly toModelOutput?: (input: ToolModelOutputInput<unknown, unknown>) => ReadonlyArray<ToolContent>
  readonly toStructuredOutput?: (output: unknown) => unknown
 }): AnyTool
 export function make(config: TypedToolConfig | DynamicToolConfig): AnyTool {
@@ -236,7 +236,7 @@ const toJsonSchema = (schema: Schema.Top): JsonSchema.JsonSchema => {
 }
 const project = (
-  toModelOutput: ((input: ToolModelOutputInput<any, any>) => ReadonlyArray<Tool.Content>) | undefined,
+  toModelOutput: ((input: ToolModelOutputInput<any, any>) => ReadonlyArray<ToolContent>) | undefined,
  toStructuredOutput: ((output: unknown) => unknown) | undefined,
  parameters: unknown,
  callID: ToolCallPart["id"],
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect, Schema, Stream } from "effect"
-import { LLM, LLMRequest, LLMResponse } from "../src"
+import { LLM, LLMResponse } from "../src"
 import { Route, Endpoint, LLMClient, Protocol, type FramingDef } from "../src/route"
 import { Model } from "../src/schema"
 import { testEffect } from "./lib/effect"
@@ -40,7 +40,7 @@ const fakeFraming: FramingDef<FakeEvent> = {
 const raiseEvent = (event: FakeEvent): import("../src/schema").LLMEvent =>
  event.type === "finish"
-    ? { type: "finish", reason: { normalized: event.reason } }
+    ? { type: "finish", reason: event.reason }
    : { type: "text-delta", id: "text-0", text: event.text }
 const fakeProtocol = Protocol.make<FakeBody, FakeEvent, FakeEvent, void>({
@@ -141,7 +141,7 @@ describe("llm route", () => {
    Effect.gen(function* () {
      const llm = yield* LLMClient.Service
      const prepared = yield* llm.prepare(
-        LLMRequest.update(request, { model: updateModel(request.model, { route: configuredGemini }) }),
+        LLM.updateRequest(request, { model: updateModel(request.model, { route: configuredGemini }) }),
      )
      expect(prepared.route).toBe("gemini-fake")
@@ -174,7 +174,7 @@ describe("llm route", () => {
      })
      const prepared = yield* (yield* LLMClient.Service).prepare(
-        LLMRequest.update(request, { model: updateModel(request.model, { route: duplicate }) }),
+        LLM.updateRequest(request, { model: updateModel(request.model, { route: duplicate }) }),
      )
      expect(prepared.body).toEqual({ body: "late-default" })
@@ -137,26 +137,15 @@ Azure.configure({ apiKey: "azure-key", resourceName: "resource" }).chat("deploym
 Azure.configure({ resourceName: "resource", apiKey: "azure-key", auth: Auth.header("api-key", "override") })
 Anthropic.configure({ apiKey: "anthropic-key" }).model("claude-haiku")
 Anthropic.configure({
  apiKey: "anthropic-key",
  providerOptions: {
    anthropic: { thinking: { type: "enabled", budgetTokens: 1_024 }, effort: "high" },
  },
 }).model("claude-haiku")
 // @ts-expect-error Anthropic model selectors only accept model ids.
 Anthropic.configure({ apiKey: "anthropic-key" }).model("claude-haiku", {})
 // @ts-expect-error Anthropic package settings accept only one auth source.
 Anthropic.model("claude-sonnet-4-6", { apiKey: "anthropic-key", authToken: "anthropic-token" })
 // @ts-expect-error Enabled Anthropic thinking requires a token budget.
 Anthropic.configure({ providerOptions: { anthropic: { thinking: { type: "enabled" } } } })
 // @ts-expect-error Anthropic thinking budgets must be numbers.
 Anthropic.configure({ providerOptions: { anthropic: { thinking: { type: "enabled", budgetTokens: "large" } } } })
 AnthropicCompatible.configure({
  apiKey: "messages-key",
  baseURL: "https://messages.example.com/v1",
  provider: "example",
  providerOptions: { anthropic: { thinking: { type: "disabled" } } },
 }).model("compatible-model")
 // @ts-expect-error Anthropic-compatible providers require a base URL.
 AnthropicCompatible.configure({ apiKey: "messages-key" })
@@ -170,19 +159,10 @@ AnthropicCompatible.model("compatible-model", {
 })
 Google.configure({ apiKey: "google-key" }).model("gemini-2.5-flash")
 Google.configure({
  apiKey: "google-key",
  providerOptions: { gemini: { thinkingConfig: { thinkingBudget: 0, includeThoughts: false } } },
 }).model("gemini-2.5-flash")
 // @ts-expect-error Google model selectors only accept model ids.
 Google.configure({ apiKey: "google-key" }).model("gemini-2.5-flash", {})
 // @ts-expect-error Gemini thinking budgets must be numbers.
 Google.configure({ providerOptions: { gemini: { thinkingConfig: { thinkingBudget: "large" } } } })
-GoogleVertex.configure({
+GoogleVertex.configure({ apiKey: "vertex-key" }).model("gemini-3.5-flash")
  apiKey: "vertex-key",
  providerOptions: { gemini: { thinkingConfig: { thinkingBudget: 1_024 } } },
 }).model("gemini-3.5-flash")
 GoogleVertex.configure({ accessToken: "vertex-token", project: "project" }).model("gemini-3.5-flash")
 GoogleVertex.configure({ auth: Auth.bearer("vertex-token"), project: "project" }).model("gemini-3.5-flash")
 // @ts-expect-error Vertex Gemini model selectors only accept model ids.
@@ -228,11 +208,7 @@ GoogleVertexResponses.configure({
  project: "project",
 })
-GoogleVertexMessages.configure({
+GoogleVertexMessages.configure({ accessToken: "vertex-token", project: "project" }).model("claude-sonnet-4-6")
  accessToken: "vertex-token",
  project: "project",
  providerOptions: { anthropic: { thinking: { type: "adaptive", display: "omitted" }, effort: "low" } },
 }).model("claude-sonnet-4-6")
 // @ts-expect-error Vertex Messages package settings do not accept API keys.
 GoogleVertexMessages.model("claude-sonnet-4-6", { apiKey: "vertex-key", project: "project" })
 GoogleVertexMessages.configure({ auth: Auth.bearer("vertex-token"), project: "project" }).model("claude-sonnet-4-6")
@@ -39,8 +39,8 @@ describe("applyCachePolicy", () => {
        }),
      )
-      // A single system block is both the first and last boundary, so the auto
+      // No explicit cache field → auto policy fires → last system part + latest
-      // policy deduplicates it and still marks the conversation tail.
+      // user message both get cache_control markers.
      expect(prepared.body).toMatchObject({
        system: [{ type: "text", text: "You are concise.", cache_control: { type: "ephemeral" } }],
        messages: [{ role: "user", content: [{ type: "text", text: "hi", cache_control: { type: "ephemeral" } }] }],
@@ -48,15 +48,12 @@ describe("applyCachePolicy", () => {
    }),
  )
-  it.effect("'auto' marks the last tool, first and last system parts, and final message boundary on Anthropic", () =>
+  it.effect("'auto' marks the last tool, last system part, and latest user message on Anthropic", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare(
        LLM.request({
          model: anthropicModel,
-          system: [
+          system: "Sys A",
            { type: "text", text: "Base agent" },
            { type: "text", text: "Project instructions" },
          ],
          tools: [{ name: "t1", description: "t1", inputSchema: { type: "object", properties: {} } }],
          messages: [
            Message.user("first user"),
@@ -69,10 +66,7 @@ describe("applyCachePolicy", () => {
      expect(prepared.body).toMatchObject({
        tools: [{ name: "t1", cache_control: { type: "ephemeral" } }],
-        system: [
+        system: [{ type: "text", text: "Sys A", cache_control: { type: "ephemeral" } }],
          { type: "text", text: "Base agent", cache_control: { type: "ephemeral" } },
          { type: "text", text: "Project instructions", cache_control: { type: "ephemeral" } },
        ],
        messages: [
          { role: "user", content: [{ type: "text", text: "first user" }] },
          { role: "assistant", content: [{ type: "text", text: "assistant reply" }] },
@@ -126,10 +120,7 @@ describe("applyCachePolicy", () => {
      const prepared = yield* LLMClient.prepare(
        LLM.request({
          model: bedrockModel,
-          system: [
+          system: "Sys",
            { type: "text", text: "Base agent" },
            { type: "text", text: "Project instructions" },
          ],
          tools: [{ name: "t1", description: "t1", inputSchema: { type: "object", properties: {} } }],
          messages: [Message.user("first user"), Message.assistant("reply"), Message.user("latest user")],
          cache: "auto",
@@ -140,12 +131,7 @@ describe("applyCachePolicy", () => {
        toolConfig: {
          tools: [{ toolSpec: { name: "t1" } }, { cachePoint: { type: "default" } }],
        },
-        system: [
+        system: [{ text: "Sys" }, { cachePoint: { type: "default" } }],
          { text: "Base agent" },
          { cachePoint: { type: "default" } },
          { text: "Project instructions" },
          { cachePoint: { type: "default" } },
        ],
        messages: [
          { role: "user", content: [{ text: "first user" }] },
          { role: "assistant", content: [{ text: "reply" }] },
@@ -207,55 +193,9 @@ describe("applyCachePolicy", () => {
        }),
      )
-      const body = prepared.body as {
+      const body = prepared.body as { system: Array<{ text: string; cache_control?: unknown }> }
        system: Array<{ text: string; cache_control?: unknown }>
        messages: Array<{ content: Array<{ cache_control?: unknown }> }>
      }
      expect(body.system[0]?.cache_control).toEqual({ type: "ephemeral", ttl: "1h" })
      expect(body.system[1]?.cache_control).toEqual({ type: "ephemeral" })
      expect(body.messages[0]?.content[0]?.cache_control).toEqual({ type: "ephemeral" })
    }),
  )
  it.effect("auto policy stays within the four-breakpoint cap when preserving manual hints", () =>
    Effect.gen(function* () {
      const request = LLM.request({
        model: anthropicModel,
        system: [
          { type: "text", text: "Base agent" },
          {
            type: "text",
            text: "Manual context",
            cache: new CacheHint({ type: "ephemeral", ttlSeconds: 3600 }),
          },
          { type: "text", text: "Project instructions" },
        ],
        tools: [{ name: "t1", description: "t1", inputSchema: { type: "object", properties: {} } }],
        prompt: "hi",
        cache: "auto",
      })
      const applied = applyCachePolicy(request)
      expect(applied.tools[0]?.cache).toBeDefined()
      expect(applied.system.map((part) => part.cache !== undefined)).toEqual([true, true, true])
      const tail = applied.messages[0]!.content[0]!
      expect("cache" in tail ? tail.cache : undefined).toBeUndefined()
      expect(applyCachePolicy(applied)).toBe(applied)
      const prepared = yield* LLMClient.prepare(request)
      const body = prepared.body as {
        tools: Array<{ cache_control?: unknown }>
        system: Array<{ cache_control?: unknown }>
        messages: Array<{ content: Array<{ cache_control?: unknown }> }>
      }
      const marked = [
        ...body.tools.map((tool) => tool.cache_control),
        ...body.system.map((part) => part.cache_control),
        ...body.messages.flatMap((message) => message.content.map((part) => part.cache_control)),
      ].filter((cache) => cache !== undefined)
      expect(marked).toHaveLength(4)
      expect(body.system[1]?.cache_control).toEqual({ type: "ephemeral", ttl: "1h" })
      expect(body.messages[0]?.content[0]?.cache_control).toBeUndefined()
    }),
  )
@@ -11,15 +11,8 @@ import {
  XAI,
 } from "@opencode-ai/ai/providers"
 import * as GitHubCopilot from "@opencode-ai/ai/providers/github-copilot"
-import {
+import { OpenAIChat, OpenAICompatibleChat, OpenAICompatibleResponses, OpenAIResponses } from "@opencode-ai/ai/protocols"
  OpenAIChat,
  OpenAICompatibleChat,
  OpenAICompatibleResponses,
  OpenAIResponses,
  OpenResponses,
 } from "@opencode-ai/ai/protocols"
 import * as AnthropicMessages from "@opencode-ai/ai/protocols/anthropic-messages"
 import { TestLLM } from "@opencode-ai/ai/testing"
 describe("public exports", () => {
  test("root exposes app-facing runtime APIs", () => {
@@ -29,7 +22,6 @@ describe("public exports", () => {
    expect(ImageInput.bytes).toBeFunction()
    expect(Provider.make).toBeFunction()
    expect(ProviderSubpath.make).toBe(Provider.make)
    expect(TestLLM.layer).toBeFunction()
  })
  test("route barrel exposes route-authoring APIs", () => {
@@ -82,9 +74,7 @@ describe("public exports", () => {
  test("protocol barrels expose supported low-level routes", () => {
    expect(OpenAIChat.route.id).toBe("openai-chat")
    expect(OpenAICompatibleChat.route.id).toBe("openai-compatible-chat")
    expect(OpenResponses.protocol.id).toBe("open-responses")
    expect(OpenAICompatibleResponses.route.id).toBe("openai-compatible-responses")
    expect(OpenAICompatibleResponses.route.protocol).toBe("open-responses")
    expect(OpenAIResponses.route.id).toBe("openai-responses")
    expect(OpenAIResponses.webSocketRoute.id).toBe("openai-responses-websocket")
    expect(AnthropicMessages.route.id).toBe("anthropic-messages")
@@ -83,7 +83,7 @@ const indexStep = (event: LLMEvent, index: number): LLMEvent => {
 const stepState = (events: ReadonlyArray<LLMEvent>) => {
  const assistantContent: ContentPart[] = []
  const toolCalls: ToolCallPart[] = []
-  let reason: Extract<LLMEvent, { type: "finish" }>["reason"] = { normalized: "unknown" }
+  let reason: Extract<LLMEvent, { type: "finish" }>["reason"] = "unknown"
  let usage: Usage | undefined
  let providerMetadata: ProviderMetadata | undefined
@@ -2,16 +2,7 @@ import { describe, expect, test } from "bun:test"
 import { CacheHint, LLM, LLMResponse } from "../src"
 import * as OpenAIChat from "../src/protocols/openai-chat"
 import * as OpenAIResponses from "../src/protocols/openai-responses"
-import {
+import { LLMRequest, Message, Model, ToolCallPart, ToolChoice, ToolDefinition, ToolResultPart } from "../src/schema"
  GenerationOptions,
  LLMRequest,
  Message,
  Model,
  ToolCallPart,
  ToolChoice,
  ToolDefinition,
  ToolResultPart,
 } from "../src/schema"
 const chatRoute = OpenAIChat.route
 const responsesRoute = OpenAIResponses.route
@@ -40,8 +31,8 @@ describe("llm constructors", () => {
      model: Model.make({ id: "fake-model", provider: "fake", route: chatRoute }),
      prompt: "Say hello.",
    })
-    const updated = LLMRequest.update(base, {
+    const updated = LLM.updateRequest(base, {
-      generation: GenerationOptions.make({ maxTokens: 20 }),
+      generation: { maxTokens: 20 },
      messages: [...base.messages, Message.assistant("Hi.")],
    })
@@ -200,7 +191,7 @@ describe("llm constructors", () => {
      LLMResponse.text({
        events: [
          { type: "text-delta", id: "text-0", text: "hi" },
-          { type: "finish", reason: { normalized: "stop" } },
+          { type: "finish", reason: "stop" },
        ],
      }),
    ).toBe("hi")
@@ -58,12 +58,6 @@ describe("provider error classification", () => {
    ).toEqual(["ProviderInternal", "ProviderInternal"])
  })
  test("classifies transient client statuses as provider internal", () => {
    expect(
      [408, 409].map((status) => classifyProviderFailure({ message: `HTTP ${status}`, status })._tag),
    ).toEqual(["ProviderInternal", "ProviderInternal"])
  })
  test("classifies nested provider codes when a top-level code is also present", () => {
    expect(
      [
@@ -59,7 +59,7 @@ describe("provider package entrypoints", () => {
      headers: { "x-application": "opencode" },
      body: { service_tier: "priority" },
      limits: { context: 200_000, output: 64_000 },
-      providerOptions: { openresponses: { reasoningEffort: "low", store: true } },
+      providerOptions: { openai: { reasoningEffort: "low", store: true } },
    })
    expect(String(selected.provider)).toBe("example")
@@ -72,7 +72,7 @@ describe("provider package entrypoints", () => {
    expect(selected.route.defaults.http?.body).toEqual({ service_tier: "priority" })
    expect(selected.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
    expect(selected.route.defaults.providerOptions).toEqual({
-      openresponses: { reasoningEffort: "low", store: true },
+      openai: { reasoningEffort: "low", store: true },
    })
  })
@@ -85,7 +85,6 @@ describe("provider package entrypoints", () => {
      headers: { "x-application": "opencode" },
      body: { metadata: { user_id: "user_1" } },
      limits: { context: 200_000, output: 64_000 },
      providerOptions: { anthropic: { effort: "low" } },
    })
    expect(String(selected.provider)).toBe("example")
@@ -97,19 +96,6 @@ describe("provider package entrypoints", () => {
    expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
    expect(selected.route.defaults.http?.body).toEqual({ metadata: { user_id: "user_1" } })
    expect(selected.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
    expect(selected.route.defaults.providerOptions).toEqual({ anthropic: { effort: "low" } })
  })
  test("maps Anthropic provider options onto the executable model", async () => {
    const Anthropic = await import("@opencode-ai/ai/providers/anthropic")
    const selected = Anthropic.model("claude-sonnet-4-6", {
      apiKey: "fixture",
      providerOptions: { anthropic: { thinking: { type: "adaptive" } } },
    })
    expect(selected.route.defaults.providerOptions).toEqual({
      anthropic: { thinking: { type: "adaptive" } },
    })
  })
  test("requires an Anthropic-compatible base URL at runtime", async () => {
@@ -249,12 +235,12 @@ describe("provider package entrypoints", () => {
      path: "/chat/completions",
    })
    expect(responses.route.id).toBe("google-vertex-responses")
-    expect(responses.route.protocol).toBe("open-responses")
+    expect(responses.route.protocol).toBe("openai-responses")
    expect(responses.route.endpoint).toMatchObject({
      baseURL: "https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi",
      path: "/responses",
    })
-    expect(responses.route.defaults.providerOptions).toEqual({ openresponses: { store: false } })
+    expect(responses.route.defaults.providerOptions).toEqual({ openai: { store: false } })
  })
  test("rejects conflicting Vertex auth settings at runtime", async () => {
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { CacheHint, LLM, LLMRequest, Message, ToolCallPart, ToolDefinition } from "../../src"
+import { CacheHint, LLM } from "../../src"
 import { LLMClient } from "../../src/route"
 import * as Anthropic from "../../src/providers/anthropic"
 import { LARGE_CACHEABLE_SYSTEM } from "../recorded-scenarios"
@@ -24,39 +24,6 @@ const cacheRequest = LLM.request({
  generation: { maxTokens: 16, temperature: 0 },
 })
 const lookup = ToolDefinition.make({
  name: "lookup",
  description: "Look up a fixture value.",
  inputSchema: {
    type: "object",
    properties: { index: { type: "number" } },
    required: ["index"],
    additionalProperties: false,
  },
 })
 const longToolTurn = [
  Message.user("Run the fixture lookups."),
  ...Array.from({ length: 11 }, (_, index) => {
    const id = `lookup_${index}`
    return [
      Message.assistant(ToolCallPart.make({ id, name: lookup.name, input: { index } })),
      Message.tool({
        id,
        name: lookup.name,
        result: `Fixture result ${index}. `.repeat(80),
      }),
    ]
  }).flat(),
 ]
 const longToolTurnRequest = LLM.request({
  id: "recorded_anthropic_cache_long_tool_turn",
  model,
  system: LARGE_CACHEABLE_SYSTEM,
  messages: longToolTurn,
  tools: [lookup],
  generation: { maxTokens: 16, temperature: 0 },
 })
 const recorded = recordedTests({
  prefix: "anthropic-messages-cache",
  provider: "anthropic",
@@ -83,28 +50,4 @@ describe("Anthropic Messages cache recorded", () => {
      expect(second.usage?.cacheReadInputTokens ?? 0).toBeGreaterThan(0)
    }),
  )
  recorded.effect.with("keeps a long tool turn inside the cache lookback", { tags: ["cache", "tool"] }, () =>
    Effect.gen(function* () {
      const first = yield* LLMClient.generate(longToolTurnRequest)
      const firstRead = first.usage?.cacheReadInputTokens ?? 0
      const firstWrite = first.usage?.cacheWriteInputTokens ?? 0
      const firstCached = firstRead + firstWrite
      // The prefix may already be warm when recording, so either a read or a
      // write establishes that Anthropic recognized the cache boundary.
      expect(firstCached).toBeGreaterThan(0)
      const second = yield* LLMClient.generate(
        LLMRequest.update(longToolTurnRequest, {
          messages: [
            ...longToolTurn,
            Message.assistant("The fixture lookups are complete."),
            Message.user("Reply exactly: OK"),
          ],
        }),
      )
      expect(second.usage?.cacheReadInputTokens ?? 0).toBeGreaterThanOrEqual(firstCached)
      expect(second.usage?.cacheWriteInputTokens ?? 0).toBeLessThan(firstCached)
    }),
  )
 })
@@ -1,7 +1,7 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
-import { CacheHint, LLM, LLMError, LLMRequest, Message, ToolCallPart, ToolDefinition, Usage } from "../../src"
+import { CacheHint, LLM, LLMError, Message, ToolCallPart, Usage } from "../../src"
 import { Auth, LLMClient } from "../../src/route"
 import * as AnthropicMessages from "../../src/protocols/anthropic-messages"
 import { continuationRequest, nativeAnthropicMessagesContinuation } from "../continuation-scenarios"
@@ -60,7 +60,7 @@ describe("Anthropic Messages route", () => {
  it.effect("lowers adaptive thinking settings with effort", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
          providerOptions: {
            anthropic: { thinking: { type: "adaptive", display: "summarized" }, effort: "low" },
          },
@@ -74,42 +74,6 @@ describe("Anthropic Messages route", () => {
    }),
  )
  it.effect("normalizes enabled and disabled thinking settings", () =>
    Effect.gen(function* () {
      const enabled = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
        LLMRequest.update(request, {
          providerOptions: { anthropic: { thinking: { type: "enabled", budgetTokens: 1_024 } } },
        }),
      )
      const legacy = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
        LLMRequest.update(request, {
          providerOptions: { anthropic: { thinking: { type: "enabled", budget_tokens: 2_048 } } },
        }),
      )
      const disabled = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
        LLMRequest.update(request, {
          providerOptions: { anthropic: { thinking: { type: "disabled" } } },
        }),
      )
      expect(enabled.body.thinking).toEqual({ type: "enabled", budget_tokens: 1_024 })
      expect(legacy.body.thinking).toEqual({ type: "enabled", budget_tokens: 2_048 })
      expect(disabled.body.thinking).toEqual({ type: "disabled" })
    }),
  )
  it.effect("rejects enabled thinking without a budget", () =>
    Effect.gen(function* () {
      const error = yield* LLMClient.prepare(
        LLMRequest.update(request, {
          providerOptions: { anthropic: { thinking: { type: "enabled" } } },
        }),
      ).pipe(Effect.flip)
      expect(error.message).toContain("Anthropic thinking provider option requires budgetTokens")
    }),
  )
  it.effect("lowers chronological system updates natively for Claude Opus 4.8 with cache hints", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
@@ -271,34 +235,6 @@ describe("Anthropic Messages route", () => {
    }),
  )
  it.effect("keeps tools and sends tool_choice none", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
        LLM.request({
          id: "req_tool_choice_none",
          model,
          tools: [{ name: "lookup", description: "Look things up", inputSchema: { type: "object", properties: {} } }],
          messages: [
            Message.user("What is the weather?"),
            Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: { query: "weather" } })]),
            Message.tool({ id: "call_1", name: "lookup", result: { forecast: "sunny" } }),
          ],
          toolChoice: "none",
          cache: "none",
        }),
      )
      expect(prepared.body.tools).toEqual([
        {
          name: "lookup",
          description: "Look things up",
          input_schema: { type: "object", properties: {} },
        },
      ])
      expect(prepared.body.tool_choice).toEqual({ type: "none" })
    }),
  )
  // Regression: read tool results must stay structured so base64 media data is
  // not JSON-stringified into `tool_result.content`.
  it.effect("lowers media tool-result content as structured blocks", () =>
@@ -445,34 +381,6 @@ describe("Anthropic Messages route", () => {
    }),
  )
  it.effect("round-trips redacted thinking as redacted_thinking blocks", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare(
        LLM.request({
          model,
          messages: [
            Message.assistant([
              { type: "reasoning", text: "", providerMetadata: { anthropic: { redactedData: "opaque_1" } } },
              { type: "reasoning", text: "visible", providerMetadata: { anthropic: { signature: "sig_1" } } },
            ]),
          ],
        }),
      )
      expect(prepared.body).toMatchObject({
        messages: [
          {
            role: "assistant",
            content: [
              { type: "redacted_thinking", data: "opaque_1" },
              { type: "thinking", thinking: "visible", signature: "sig_1" },
            ],
          },
        ],
      })
    }),
  )
  it.effect("parses text, reasoning, and usage stream fixtures", () =>
    Effect.gen(function* () {
      const body = sseEvents(
@@ -506,351 +414,18 @@ describe("Anthropic Messages route", () => {
      expect(response.events.find((event) => event.type === "reasoning-end")).toMatchObject({
        providerMetadata: { anthropic: { signature: "sig_1" } },
      })
      expect(response.events.find((event) => event.type === "reasoning-delta" && event.text === "")).toBeUndefined()
      expect(response.message.content).toEqual([
        { type: "text", text: "Hello!" },
        { type: "reasoning", text: "thinking", providerMetadata: { anthropic: { signature: "sig_1" } } },
      ])
      expect(response.events.at(-1)).toMatchObject({
        type: "finish",
-        reason: { normalized: "stop", raw: "end_turn" },
+        reason: "stop",
        providerMetadata: { anthropic: { stopSequence: "\n\nHuman:" } },
      })
    }),
  )
  it.effect("requires message_stop before completing a streamed message", () =>
    Effect.gen(function* () {
      const error = yield* LLMClient.generate(request).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              { type: "message_start", message: { usage: { input_tokens: 5 } } },
              { type: "content_block_start", index: 0, content_block: { type: "text", text: "" } },
              { type: "content_block_delta", index: 0, delta: { type: "text_delta", text: "Hello" } },
              { type: "content_block_stop", index: 0 },
              { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
            ),
          ),
        ),
        Effect.flip,
      )
      expect(error.reason).toMatchObject({
        _tag: "InvalidProviderOutput",
        message: "Provider stream ended without a terminal finish event",
      })
    }),
  )
  it.effect("maps thinking tokens and preserves unknown Anthropic usage fields", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(request).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              {
                type: "message_start",
                message: {
                  usage: {
                    input_tokens: 5,
                    cache_read_input_tokens: 2,
                    service_tier: "standard",
                    cache_creation: { ephemeral_5m_input_tokens: 1 },
                    server_tool_use: { web_search_requests: 1, start_counter: 2 },
                    output_tokens_details: { thinking_tokens: 3, start_detail: "preserved" },
                  },
                },
              },
              {
                type: "message_delta",
                delta: { stop_reason: "end_turn" },
                usage: {
                  output_tokens: 8,
                  server_tool_use: { web_search_requests: 2, terminal_counter: 3 },
                  output_tokens_details: { terminal_detail: "preserved" },
                  future_terminal: { requests: 4 },
                },
              },
              { type: "message_stop" },
            ),
          ),
        ),
      )
      expect(response.usage).toMatchObject({
        inputTokens: 7,
        outputTokens: 8,
        reasoningTokens: 3,
        totalTokens: 15,
        providerMetadata: {
          anthropic: {
            input_tokens: 5,
            cache_read_input_tokens: 2,
            service_tier: "standard",
            cache_creation: { ephemeral_5m_input_tokens: 1 },
            server_tool_use: { web_search_requests: 2, start_counter: 2, terminal_counter: 3 },
            output_tokens: 8,
            output_tokens_details: {
              thinking_tokens: 3,
              start_detail: "preserved",
              terminal_detail: "preserved",
            },
            future_terminal: { requests: 4 },
          },
        },
      })
    }),
  )
  it.effect("round-trips omitted thinking carried only by a signature delta", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(request).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              { type: "message_start", message: { usage: { input_tokens: 5 } } },
              {
                type: "content_block_start",
                index: 0,
                content_block: { type: "thinking", thinking: "", signature: "" },
              },
              { type: "content_block_delta", index: 0, delta: { type: "signature_delta", signature: "sig_1" } },
              { type: "content_block_stop", index: 0 },
              { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
              { type: "message_stop" },
            ),
          ),
        ),
      )
      expect(response.message.content).toEqual([
        { type: "reasoning", text: "", providerMetadata: { anthropic: { signature: "sig_1" } } },
      ])
      const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
        LLM.request({ model, messages: [response.message], cache: "none" }),
      )
      expect(prepared.body.messages).toEqual([
        { role: "assistant", content: [{ type: "thinking", thinking: "", signature: "sig_1" }] },
      ])
    }),
  )
  it.effect("retains a thinking signature supplied in content_block_start", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(request).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              { type: "message_start", message: { usage: { input_tokens: 5 } } },
              {
                type: "content_block_start",
                index: 0,
                content_block: { type: "thinking", thinking: "", signature: "sig_1" },
              },
              { type: "content_block_stop", index: 0 },
              { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
              { type: "message_stop" },
            ),
          ),
        ),
      )
      expect(response.message.content).toEqual([
        { type: "reasoning", text: "", providerMetadata: { anthropic: { signature: "sig_1" } } },
      ])
      expect(response.events.find((event) => event.type === "reasoning-end")).toMatchObject({
        providerMetadata: { anthropic: { signature: "sig_1" } },
      })
    }),
  )
  it.effect("retains complete tool input from content_block_start", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(request).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              { type: "message_start", message: { usage: { input_tokens: 5 } } },
              {
                type: "content_block_start",
                index: 0,
                content_block: { type: "tool_use", id: "call_1", name: "lookup", input: { query: "weather" } },
              },
              { type: "content_block_stop", index: 0 },
              { type: "message_delta", delta: { stop_reason: "tool_use" }, usage: { output_tokens: 1 } },
              { type: "message_stop" },
            ),
          ),
        ),
      )
      expect(response.toolCalls).toMatchObject([
        { id: "call_1", name: "lookup", input: { query: "weather" } },
      ])
    }),
  )
  it.effect("retains empty text blocks", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(request).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              { type: "message_start", message: { usage: { input_tokens: 5 } } },
              { type: "content_block_start", index: 0, content_block: { type: "text", text: "" } },
              { type: "content_block_stop", index: 0 },
              { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
              { type: "message_stop" },
            ),
          ),
        ),
      )
      expect(response.message.content).toEqual([{ type: "text", text: "" }])
    }),
  )
  it.effect("parses redacted thinking into empty reasoning with redactedData metadata", () =>
    Effect.gen(function* () {
      const body = sseEvents(
        { type: "message_start", message: { usage: { input_tokens: 5 } } },
        { type: "content_block_start", index: 0, content_block: { type: "redacted_thinking", data: "opaque_1" } },
        { type: "content_block_stop", index: 0 },
        { type: "content_block_start", index: 1, content_block: { type: "text", text: "" } },
        { type: "content_block_delta", index: 1, delta: { type: "text_delta", text: "Hello" } },
        { type: "content_block_stop", index: 1 },
        { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 2 } },
        { type: "message_stop" },
      )
      const response = yield* LLMClient.generate(request).pipe(Effect.provide(fixedResponse(body)))
      expect(response.events.find((event) => event.type === "reasoning-start")).toMatchObject({
        providerMetadata: { anthropic: { redactedData: "opaque_1" } },
      })
      expect(response.message.content).toEqual([
        { type: "reasoning", text: "", providerMetadata: { anthropic: { redactedData: "opaque_1" } } },
        { type: "text", text: "Hello" },
      ])
    }),
  )
  it.effect("round-trips streamed redacted thinking with tool use into a continuation request", () =>
    Effect.gen(function* () {
      // Anthropic types `redacted_thinking.data` as an opaque string. Its
      // contents are provider-owned and must be replayed without inspection.
      const redactedData = "cmVkYWN0ZWQtdGhpbmtpbmc="
      const response = yield* LLMClient.generate(
        LLMRequest.update(request, {
          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
        }),
      ).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              { type: "message_start", message: { usage: { input_tokens: 5 } } },
              {
                type: "content_block_start",
                index: 0,
                content_block: { type: "redacted_thinking", data: redactedData },
              },
              { type: "content_block_stop", index: 0 },
              {
                type: "content_block_start",
                index: 1,
                content_block: { type: "tool_use", id: "call_1", name: "lookup" },
              },
              {
                type: "content_block_delta",
                index: 1,
                delta: { type: "input_json_delta", partial_json: '{"query":"weather"}' },
              },
              { type: "content_block_stop", index: 1 },
              { type: "message_delta", delta: { stop_reason: "tool_use" }, usage: { output_tokens: 1 } },
              { type: "message_stop" },
            ),
          ),
        ),
      )
      const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
        LLM.request({
          model,
          messages: [
            Message.user("Say hello."),
            response.message,
            Message.tool({ id: "call_1", name: "lookup", result: "sunny", resultType: "text" }),
          ],
          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
          cache: "none",
        }),
      )
      expect(prepared.body.messages).toEqual([
        { role: "user", content: [{ type: "text", text: "Say hello." }] },
        {
          role: "assistant",
          content: [
            { type: "redacted_thinking", data: redactedData },
            { type: "tool_use", id: "call_1", name: "lookup", input: { query: "weather" } },
          ],
        },
        {
          role: "user",
          content: [
            {
              type: "tool_result",
              tool_use_id: "call_1",
              content: "sunny",
              is_error: undefined,
              cache_control: undefined,
            },
          ],
        },
      ])
    }),
  )
  it.effect("maps context-window truncation to length", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(request).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              { type: "message_start", message: { usage: { input_tokens: 5 } } },
              {
                type: "message_delta",
                delta: { stop_reason: "model_context_window_exceeded" },
                usage: { output_tokens: 1 },
              },
              { type: "message_stop" },
            ),
          ),
        ),
      )
      expect(response.finishReason).toEqual({ normalized: "length", raw: "model_context_window_exceeded" })
    }),
  )
  it.effect("preserves pause_turn while normalizing it to stop", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(request).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              { type: "message_start", message: { usage: { input_tokens: 5 } } },
              { type: "message_delta", delta: { stop_reason: "pause_turn" }, usage: { output_tokens: 1 } },
              { type: "message_stop" },
            ),
          ),
        ),
      )
      expect(response.finishReason).toEqual({ normalized: "stop", raw: "pause_turn" })
    }),
  )
  it.effect("assembles streamed tool call input", () =>
    Effect.gen(function* () {
      const body = sseEvents(
@@ -860,11 +435,10 @@ describe("Anthropic Messages route", () => {
        { type: "content_block_delta", index: 0, delta: { type: "input_json_delta", partial_json: ':"weather"}' } },
        { type: "content_block_stop", index: 0 },
        { type: "message_delta", delta: { stop_reason: "tool_use" }, usage: { output_tokens: 1 } },
        { type: "message_stop" },
      )
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
      const usage = new Usage({
@@ -901,16 +475,10 @@ describe("Anthropic Messages route", () => {
          providerExecuted: undefined,
          providerMetadata: undefined,
        },
-        {
+        { type: "step-finish", index: 0, reason: "tool-calls", usage, providerMetadata: undefined },
          type: "step-finish",
          index: 0,
          reason: { normalized: "tool-calls", raw: "tool_use" },
          usage,
          providerMetadata: undefined,
        },
        {
          type: "finish",
-          reason: { normalized: "tool-calls", raw: "tool_use" },
+          reason: "tool-calls",
          providerMetadata: undefined,
          usage,
        },
@@ -1046,13 +614,10 @@ describe("Anthropic Messages route", () => {
        { type: "content_block_delta", index: 2, delta: { type: "text_delta", text: "Found it." } },
        { type: "content_block_stop", index: 2 },
        { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 8 } },
        { type: "message_stop" },
      )
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [
+          tools: [{ name: "web_search", description: "Web search", inputSchema: { type: "object" } }],
            ToolDefinition.make({ name: "web_search", description: "Web search", inputSchema: { type: "object" } }),
          ],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
@@ -1071,20 +636,10 @@ describe("Anthropic Messages route", () => {
        name: "web_search",
        result: { type: "json", value: [{ type: "web_search_result", url: "https://example.com", title: "Example" }] },
        providerExecuted: true,
-        // The complete payload rides in provider metadata as irreducible replay
+        providerMetadata: { anthropic: { blockType: "web_search_tool_result" } },
        // state for later stateless requests.
        providerMetadata: {
          anthropic: {
            blockType: "web_search_tool_result",
            result: [{ type: "web_search_result", url: "https://example.com", title: "Example" }],
          },
        },
      })
      expect(response.text).toBe("Found it.")
-      expect(response.events.at(-1)).toMatchObject({
+      expect(response.events.at(-1)).toMatchObject({ type: "finish", reason: "stop" })
        type: "finish",
        reason: { normalized: "stop", raw: "end_turn" },
      })
    }),
  )
@@ -1110,13 +665,10 @@ describe("Anthropic Messages route", () => {
        },
        { type: "content_block_stop", index: 1 },
        { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
        { type: "message_stop" },
      )
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [
+          tools: [{ name: "web_search", description: "Web search", inputSchema: { type: "object" } }],
            ToolDefinition.make({ name: "web_search", description: "Web search", inputSchema: { type: "object" } }),
          ],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
@@ -1232,10 +784,7 @@ describe("Anthropic Messages route", () => {
                    content: [
                      { type: "text", text: "What is in this image?" },
                      { type: "image", source: { type: "base64", media_type: "image/png", data: "AAECAw==" } },
-                      {
+                      { type: "document", source: { type: "base64", media_type: "application/pdf", data: "JVBERi0xLjQ=" } },
                        type: "document",
                        source: { type: "base64", media_type: "application/pdf", data: "JVBERi0xLjQ=" },
                      },
                    ],
                  },
                ],
@@ -2,16 +2,7 @@ import { EventStreamCodec } from "@smithy/eventstream-codec"
 import { fromUtf8, toUtf8 } from "@smithy/util-utf8"
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import {
+import { CacheHint, LLM, Message, ToolCallPart, ToolChoice } from "../../src"
  CacheHint,
  GenerationOptions,
  LLM,
  LLMRequest,
  Message,
  ToolCallPart,
  ToolChoice,
  ToolDefinition,
 } from "../../src"
 import { LLMClient } from "../../src/route"
 import { AmazonBedrock } from "../../src/providers"
 import * as BedrockConverse from "../../src/protocols/bedrock-converse"
@@ -43,26 +34,6 @@ const eventFrame = (type: string, payload: object) =>
    body: utf8Encoder.encode(JSON.stringify(payload)),
  })
 const exceptionFrame = (type: string, payload: object) =>
  codec.encode({
    headers: {
      ":message-type": { type: "string", value: "exception" },
      ":exception-type": { type: "string", value: type },
      ":content-type": { type: "string", value: "application/json" },
    },
    body: utf8Encoder.encode(JSON.stringify(payload)),
  })
 const errorFrame = (code: string, message: string) =>
  codec.encode({
    headers: {
      ":message-type": { type: "string", value: "error" },
      ":error-code": { type: "string", value: code },
      ":error-message": { type: "string", value: message },
    },
    body: new Uint8Array(),
  })
 const concat = (frames: ReadonlyArray<Uint8Array>) => {
  const total = frames.reduce((sum, frame) => sum + frame.length, 0)
  const out = new Uint8Array(total)
@@ -115,9 +86,7 @@ describe("Bedrock Converse route", () => {
  it.effect("passes topK through additionalModelRequestFields as top_k", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare<BedrockConverse.BedrockConverseBody>(
-        LLMRequest.update(baseRequest, {
+        LLM.updateRequest(baseRequest, { generation: { maxTokens: 64, temperature: 0, topK: 40 } }),
          generation: GenerationOptions.make({ maxTokens: 64, temperature: 0, topK: 40 }),
        }),
      )
      // Converse's inferenceConfig has no topK; Anthropic/Nova read it from
@@ -154,13 +123,13 @@ describe("Bedrock Converse route", () => {
  it.effect("prepares tool config with toolSpec and toolChoice", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare(
-        LLMRequest.update(baseRequest, {
+        LLM.updateRequest(baseRequest, {
          tools: [
-            ToolDefinition.make({
+            {
              name: "lookup",
              description: "Lookup data",
              inputSchema: { type: "object", properties: { query: { type: "string" } }, required: ["query"] },
-            }),
+            },
          ],
          toolChoice: ToolChoice.make({ type: "required" }),
        }),
@@ -185,36 +154,6 @@ describe("Bedrock Converse route", () => {
    }),
  )
  it.effect("keeps tools and omits the unsupported choice when tool choice is none", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare(
        LLMRequest.update(baseRequest, {
          tools: [
            ToolDefinition.make({
              name: "lookup",
              description: "Lookup data",
              inputSchema: { type: "object", properties: { query: { type: "string" } } },
            }),
          ],
          toolChoice: ToolChoice.make({ type: "none" }),
        }),
      )
      expect(prepared.body.toolConfig).toMatchObject({
        tools: [
          {
            toolSpec: {
              name: "lookup",
              description: "Lookup data",
              inputSchema: { json: { type: "object", properties: { query: { type: "string" } } } },
            },
          },
        ],
      })
      expect(prepared.body.toolConfig?.toolChoice).toBeUndefined()
    }),
  )
  it.effect("lowers assistant tool-call + tool-result message history", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare(
@@ -321,10 +260,7 @@ describe("Bedrock Converse route", () => {
      // `metadata` (carries usage). We consolidate them into a single
      // terminal `finish` event with both.
      expect(finishes).toHaveLength(1)
-      expect(finishes[0]).toMatchObject({
+      expect(finishes[0]).toMatchObject({ type: "finish", reason: "stop" })
        type: "finish",
        reason: { normalized: "stop", raw: "end_turn" },
      })
      expect(response.usage).toMatchObject({
        inputTokens: 5,
        outputTokens: 2,
@@ -333,23 +269,6 @@ describe("Bedrock Converse route", () => {
    }),
  )
  it.effect("maps truncation and malformed output stop reasons", () =>
    Effect.gen(function* () {
      const reasons = [
        ["model_context_window_exceeded", "length"],
        ["malformed_model_output", "error"],
        ["malformed_tool_use", "error"],
      ] as const
      for (const [raw, normalized] of reasons) {
        const response = yield* LLMClient.generate(baseRequest).pipe(
          Effect.provide(fixedBytes(eventStreamBody(["messageStop", { stopReason: raw }]))),
        )
        expect(response.finishReason).toEqual({ normalized, raw })
      }
    }),
  )
  it.effect("adds cache reads and writes to Bedrock input usage", () =>
    Effect.gen(function* () {
      const body = eventStreamBody(
@@ -383,19 +302,6 @@ describe("Bedrock Converse route", () => {
    }),
  )
  it.effect("preserves usage across later metadata events without usage", () =>
    Effect.gen(function* () {
      const body = eventStreamBody(
        ["messageStop", { stopReason: "end_turn" }],
        ["metadata", { usage: { inputTokens: 5, outputTokens: 2, totalTokens: 7 } }],
        ["metadata", { metrics: { latencyMs: 100 } }],
      )
      const response = yield* LLMClient.generate(baseRequest).pipe(Effect.provide(fixedBytes(body)))
      expect(response.usage).toMatchObject({ inputTokens: 5, outputTokens: 2, totalTokens: 7 })
    }),
  )
  it.effect("assembles streamed tool call input", () =>
    Effect.gen(function* () {
      const body = eventStreamBody(
@@ -413,8 +319,8 @@ describe("Bedrock Converse route", () => {
        ["messageStop", { stopReason: "tool_use" }],
      )
      const response = yield* LLMClient.generate(
-        LLMRequest.update(baseRequest, {
+        LLM.updateRequest(baseRequest, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedBytes(body)))
@@ -426,10 +332,7 @@ describe("Bedrock Converse route", () => {
        { type: "tool-input-delta", id: "tool_1", name: "lookup", text: '{"query"' },
        { type: "tool-input-delta", id: "tool_1", name: "lookup", text: ':"weather"}' },
      ])
-      expect(response.events.at(-1)).toMatchObject({
+      expect(response.events.at(-1)).toMatchObject({ type: "finish", reason: "tool-calls" })
        type: "finish",
        reason: { normalized: "tool-calls", raw: "tool_use" },
      })
    }),
  )
@@ -455,7 +358,7 @@ describe("Bedrock Converse route", () => {
        name: "lookup",
        raw: '{"query":"partial',
      })
-      expect(response.finishReason).toEqual({ normalized: "tool-calls", raw: "end_turn" })
+      expect(response.finishReason).toBe("tool-calls")
    }),
  )
@@ -511,170 +414,12 @@ describe("Bedrock Converse route", () => {
    }),
  )
  it.effect("preserves reasoning signatures when contentBlockStop is missing", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(baseRequest).pipe(
        Effect.provide(
          fixedBytes(
            eventStreamBody(
              ["messageStart", { role: "assistant" }],
              [
                "contentBlockDelta",
                { contentBlockIndex: 0, delta: { reasoningContent: { text: "Let me think." } } },
              ],
              [
                "contentBlockDelta",
                { contentBlockIndex: 0, delta: { reasoningContent: { signature: "sig_1" } } },
              ],
              ["messageStop", { stopReason: "end_turn" }],
            ),
          ),
        ),
      )
      expect(response.events.find((event) => event.type === "reasoning-delta" && event.text === "")).toEqual({
        type: "reasoning-delta",
        id: "reasoning-0",
        text: "",
        providerMetadata: { bedrock: { signature: "sig_1" } },
      })
      expect(response.message.content).toEqual([
        {
          type: "reasoning",
          text: "Let me think.",
          providerMetadata: { bedrock: { signature: "sig_1" } },
        },
      ])
      const prepared = yield* LLMClient.prepare<BedrockConverse.BedrockConverseBody>(
        LLM.request({ model, messages: [response.message], cache: "none" }),
      )
      expect(prepared.body.messages).toEqual([
        {
          role: "assistant",
          content: [{ reasoningContent: { reasoningText: { text: "Let me think.", signature: "sig_1" } } }],
        },
      ])
    }),
  )
  it.effect("preserves signature-only reasoning blocks", () =>
    Effect.gen(function* () {
      const body = eventStreamBody(
        ["messageStart", { role: "assistant" }],
        [
          "contentBlockDelta",
          { contentBlockIndex: 0, delta: { reasoningContent: { signature: "sig_1" } } },
        ],
        ["contentBlockStop", { contentBlockIndex: 0 }],
        ["messageStop", { stopReason: "end_turn" }],
      )
      const response = yield* LLMClient.generate(baseRequest).pipe(Effect.provide(fixedBytes(body)))
      expect(response.message.content).toEqual([
        { type: "reasoning", text: "", providerMetadata: { bedrock: { signature: "sig_1" } } },
      ])
    }),
  )
  it.effect("accepts Vercel-compatible redacted reasoning data deltas", () =>
    Effect.gen(function* () {
      const redactedData = "cmVkYWN0ZWQtdGhpbmtpbmc="
      const body = eventStreamBody(
        ["messageStart", { role: "assistant" }],
        ["contentBlockDelta", { contentBlockIndex: 0, delta: { reasoningContent: { data: redactedData } } }],
        ["contentBlockStop", { contentBlockIndex: 0 }],
        ["messageStop", { stopReason: "end_turn" }],
      )
      const response = yield* LLMClient.generate(baseRequest).pipe(Effect.provide(fixedBytes(body)))
      expect(response.events.find((event) => event.type === "reasoning-delta" && event.text === "")).toEqual({
        type: "reasoning-delta",
        id: "reasoning-0",
        text: "",
        providerMetadata: { bedrock: { redactedData } },
      })
      expect(response.message.content).toEqual([
        { type: "reasoning", text: "", providerMetadata: { bedrock: { redactedData } } },
      ])
    }),
  )
  it.effect("round-trips streamed redacted reasoning with tool use into a continuation request", () =>
    Effect.gen(function* () {
      // Bedrock represents redactedContent blobs as base64 strings on its JSON
      // wire. The provider owns the payload and requires byte-exact replay.
      const redactedData = "cmVkYWN0ZWQtdGhpbmtpbmc="
      const response = yield* LLMClient.generate(
        LLMRequest.update(baseRequest, {
          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
        }),
      ).pipe(
        Effect.provide(
          fixedBytes(
            eventStreamBody(
              ["messageStart", { role: "assistant" }],
              [
                "contentBlockDelta",
                { contentBlockIndex: 0, delta: { reasoningContent: { redactedContent: redactedData } } },
              ],
              ["contentBlockStop", { contentBlockIndex: 0 }],
              [
                "contentBlockStart",
                {
                  contentBlockIndex: 1,
                  start: { toolUse: { toolUseId: "tool_1", name: "lookup" } },
                },
              ],
              ["contentBlockDelta", { contentBlockIndex: 1, delta: { toolUse: { input: '{"query":"weather"}' } } }],
              ["contentBlockStop", { contentBlockIndex: 1 }],
              ["messageStop", { stopReason: "tool_use" }],
            ),
          ),
        ),
      )
      expect(response.events.find((event) => event.type === "reasoning-delta" && event.text === "")).toEqual({
        type: "reasoning-delta",
        id: "reasoning-0",
        text: "",
        providerMetadata: { bedrock: { redactedData } },
      })
      const prepared = yield* LLMClient.prepare<BedrockConverse.BedrockConverseBody>(
        LLM.request({
          model,
          messages: [
            Message.user("Say hello."),
            response.message,
            Message.tool({ id: "tool_1", name: "lookup", result: "sunny", resultType: "text" }),
          ],
          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
          cache: "none",
        }),
      )
      expect(prepared.body.messages).toEqual([
        { role: "user", content: [{ text: "Say hello." }] },
        {
          role: "assistant",
          content: [
            { reasoningContent: { redactedContent: redactedData } },
            { toolUse: { toolUseId: "tool_1", name: "lookup", input: { query: "weather" } } },
          ],
        },
        {
          role: "user",
          content: [{ toolResult: { toolUseId: "tool_1", content: [{ text: "sunny" }], status: "success" } }],
        },
      ])
    }),
  )
  it.effect("classifies throttlingException as a rate limit", () =>
    Effect.gen(function* () {
-      const body = concat([
+      const body = eventStreamBody(
-        eventFrame("messageStart", { role: "assistant" }),
+        ["messageStart", { role: "assistant" }],
-        exceptionFrame("throttlingException", { message: "Slow down" }),
+        ["throttlingException", { message: "Slow down" }],
-      ])
+      )
      const error = yield* LLMClient.generate(baseRequest).pipe(Effect.provide(fixedBytes(body)), Effect.flip)
      expect(error.reason).toMatchObject({ _tag: "RateLimit", message: "Slow down" })
@@ -685,7 +430,7 @@ describe("Bedrock Converse route", () => {
    Effect.gen(function* () {
      const error = yield* LLMClient.generate(baseRequest).pipe(
        Effect.provide(
-          fixedBytes(exceptionFrame("validationException", { message: "Input is too long for requested model" })),
+          fixedBytes(eventStreamBody(["validationException", { message: "Input is too long for requested model" }])),
        ),
        Effect.flip,
      )
@@ -698,44 +443,12 @@ describe("Bedrock Converse route", () => {
    }),
  )
  it.effect("uses originalMessage from model stream exception frames", () =>
    Effect.gen(function* () {
      const error = yield* LLMClient.generate(baseRequest).pipe(
        Effect.provide(
          fixedBytes(
            exceptionFrame("modelStreamErrorException", {
              originalMessage: "Upstream model failed",
              originalStatusCode: 500,
            }),
          ),
        ),
        Effect.flip,
      )
      expect(error.reason).toMatchObject({ _tag: "ProviderInternal", message: "Upstream model failed" })
    }),
  )
  it.effect("fails unmodeled AWS event-stream errors", () =>
    Effect.gen(function* () {
      const error = yield* LLMClient.generate(baseRequest).pipe(
        Effect.provide(fixedBytes(errorFrame("BadStream", "Stream failed"))),
        Effect.flip,
      )
      expect(error.reason).toMatchObject({
        _tag: "InvalidProviderOutput",
        message: "BadStream: Stream failed",
      })
    }),
  )
  it.effect("rejects requests with no auth path", () =>
    Effect.gen(function* () {
      const unsignedModel = AmazonBedrock.configure({
        baseURL: "https://bedrock-runtime.test",
      }).model("anthropic.claude-3-5-sonnet-20240620-v1:0")
-      const error = yield* LLMClient.generate(LLMRequest.update(baseRequest, { model: unsignedModel })).pipe(
+      const error = yield* LLMClient.generate(LLM.updateRequest(baseRequest, { model: unsignedModel })).pipe(
        Effect.provide(fixedBytes(eventStreamBody(["messageStop", { stopReason: "end_turn" }]))),
        Effect.flip,
      )
@@ -754,7 +467,7 @@ describe("Bedrock Converse route", () => {
          secretAccessKey: "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
        },
      }).model("anthropic.claude-3-5-sonnet-20240620-v1:0")
-      const prepared = yield* LLMClient.prepare(LLMRequest.update(baseRequest, { model: signed }))
+      const prepared = yield* LLMClient.prepare(LLM.updateRequest(baseRequest, { model: signed }))
      expect(prepared.route).toBe("bedrock-converse")
      expect(prepared.model).toBe(signed)
@@ -939,7 +652,6 @@ describe("Bedrock Converse route", () => {
      const prepared = yield* LLMClient.prepare<BedrockConverse.BedrockConverseBody>(
        LLM.request({
          model,
          cache: "none",
          messages: [
            Message.assistant([ToolCallPart.make({ id: "call_1", name: "read", input: { path: "report.pdf" } })]),
            Message.tool({
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { LLM, LLMError, LLMRequest, Message, ToolCallPart, ToolDefinition, Usage } from "../../src"
+import { LLM, LLMError, Message, ToolCallPart, Usage } from "../../src"
 import { Auth, LLMClient } from "../../src/route"
 import * as Gemini from "../../src/protocols/gemini"
 import { ProviderShared } from "../../src/protocols/shared"
@@ -36,27 +36,6 @@ describe("Gemini route", () => {
    }),
  )
  it.effect("normalizes Gemini thinking options", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare<Gemini.GeminiBody>(
        LLMRequest.update(request, {
          providerOptions: { gemini: { thinkingConfig: { thinkingBudget: 0, includeThoughts: false } } },
        }),
      )
      const filtered = yield* LLMClient.prepare<Gemini.GeminiBody>(
        LLMRequest.update(request, {
          providerOptions: { gemini: { thinkingConfig: { thinkingBudget: "invalid", includeThoughts: false } } },
        }),
      )
      expect(prepared.body.generationConfig?.thinkingConfig).toEqual({
        thinkingBudget: 0,
        includeThoughts: false,
      })
      expect(filtered.body.generationConfig?.thinkingConfig).toEqual({ includeThoughts: false })
    }),
  )
  it.effect("lowers chronological system updates to wrapped user text in order", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare<Gemini.GeminiBody>(
@@ -254,22 +233,20 @@ describe("Gemini route", () => {
    }),
  )
-  it.effect("keeps tools and sends function calling mode NONE", () =>
+  it.effect("omits tools when tool choice is none", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare(
        LLM.request({
-          id: "req_tool_choice_none",
+          id: "req_no_tools",
          model,
          prompt: "Say hello.",
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
          toolChoice: { type: "none" },
        }),
      )
-      expect(prepared.body).toMatchObject({
+      expect(prepared.body).toEqual({
        contents: [{ role: "user", parts: [{ text: "Say hello." }] }],
        tools: [{ functionDeclarations: [{ name: "lookup", description: "Lookup data" }] }],
        toolConfig: { functionCallingConfig: { mode: "NONE" } },
      })
    }),
  )
@@ -394,16 +371,10 @@ describe("Gemini route", () => {
        { type: "text-delta", id: "text-0", text: "Hello" },
        { type: "text-delta", id: "text-0", text: "!" },
        { type: "text-end", id: "text-0" },
-        {
+        { type: "step-finish", index: 0, reason: "stop", usage, providerMetadata: undefined },
          type: "step-finish",
          index: 0,
          reason: { normalized: "stop", raw: "STOP" },
          usage,
          providerMetadata: undefined,
        },
        {
          type: "finish",
-          reason: { normalized: "stop", raw: "STOP" },
+          reason: "stop",
          usage,
        },
      ])
@@ -431,8 +402,8 @@ describe("Gemini route", () => {
        ],
      })
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
      const reasoning = response.events.find((event) => event.type === "reasoning-start")
@@ -522,8 +493,8 @@ describe("Gemini route", () => {
        usageMetadata: { promptTokenCount: 5, candidatesTokenCount: 1 },
      })
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
      const usage = new Usage({
@@ -556,16 +527,10 @@ describe("Gemini route", () => {
          providerExecuted: undefined,
          providerMetadata: undefined,
        },
-        {
+        { type: "step-finish", index: 0, reason: "tool-calls", usage, providerMetadata: undefined },
          type: "step-finish",
          index: 0,
          reason: { normalized: "tool-calls", raw: "STOP" },
          usage,
          providerMetadata: undefined,
        },
        {
          type: "finish",
-          reason: { normalized: "tool-calls", raw: "STOP" },
+          reason: "tool-calls",
          usage,
        },
      ])
@@ -589,8 +554,8 @@ describe("Gemini route", () => {
        ],
      })
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
@@ -604,10 +569,7 @@ describe("Gemini route", () => {
        },
        { type: "tool-call", id: "tool_1", name: "lookup", input: { query: "news" } },
      ])
-      expect(response.events.at(-1)).toMatchObject({
+      expect(response.events.at(-1)).toMatchObject({ type: "finish", reason: "tool-calls" })
        type: "finish",
        reason: { normalized: "tool-calls", raw: "STOP" },
      })
    }),
  )
@@ -627,41 +589,9 @@ describe("Gemini route", () => {
      )
      expect(length.events.map((event) => event.type)).toEqual(["step-start", "step-finish", "finish"])
-      expect(length.events.at(-1)).toMatchObject({
+      expect(length.events.at(-1)).toMatchObject({ type: "finish", reason: "length" })
        type: "finish",
        reason: { normalized: "length", raw: "MAX_TOKENS" },
      })
      expect(filtered.events.map((event) => event.type)).toEqual(["step-start", "step-finish", "finish"])
-      expect(filtered.events.at(-1)).toMatchObject({
+      expect(filtered.events.at(-1)).toMatchObject({ type: "finish", reason: "content-filter" })
        type: "finish",
        reason: { normalized: "content-filter", raw: "SAFETY" },
      })
    }),
  )
  it.effect("maps current blocking and invalid-output finish reasons", () =>
    Effect.gen(function* () {
      const reasons = [
        ["MODEL_ARMOR", "content-filter"],
        ["IMAGE_PROHIBITED_CONTENT", "content-filter"],
        ["IMAGE_RECITATION", "content-filter"],
        ["LANGUAGE", "content-filter"],
        ["UNEXPECTED_TOOL_CALL", "error"],
        ["NO_IMAGE", "error"],
        ["IMAGE_OTHER", "unknown"],
        ["TOO_MANY_TOOL_CALLS", "error"],
        ["MISSING_THOUGHT_SIGNATURE", "error"],
        ["MALFORMED_RESPONSE", "error"],
      ] as const
      for (const [raw, normalized] of reasons) {
        const response = yield* LLMClient.generate(request).pipe(
          Effect.provide(
            fixedResponse(sseEvents({ candidates: [{ content: { role: "model", parts: [] }, finishReason: raw }] })),
          ),
        )
        expect(response.finishReason).toEqual({ normalized, raw })
      }
    }),
  )
@@ -1,18 +1,7 @@
 import { describe, expect } from "bun:test"
 import { Effect, Schema, Stream } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
-import {
+import { LLM, LLMError, LLMEvent, Message, Model, ToolCallPart, Usage } from "../../src"
  HttpOptions,
  LLM,
  LLMError,
  LLMEvent,
  LLMRequest,
  Message,
  Model,
  ToolCallPart,
  ToolDefinition,
  Usage,
 } from "../../src"
 import * as Azure from "../../src/providers/azure"
 import * as OpenAI from "../../src/providers/openai"
 import * as OpenAIChat from "../../src/protocols/openai-chat"
@@ -173,7 +162,7 @@ describe("OpenAI Chat route", () => {
  it.effect("adds native query params to the Chat Completions URL", () =>
    LLMClient.generate(
-      LLMRequest.update(request, {
+      LLM.updateRequest(request, {
        model: Model.update(model, { route: model.route.with({ endpoint: { query: { "api-version": "v1" } } }) }),
      }),
    ).pipe(
@@ -193,7 +182,7 @@ describe("OpenAI Chat route", () => {
  it.effect("uses Azure api-key header for static OpenAI Chat keys", () =>
    LLMClient.generate(
-      LLMRequest.update(request, {
+      LLM.updateRequest(request, {
        model: Azure.configure({
          baseURL: "https://opencode-test.openai.azure.com/openai/v1/",
          apiKey: "azure-key",
@@ -219,15 +208,15 @@ describe("OpenAI Chat route", () => {
  it.effect("applies serializable HTTP overlays after payload lowering", () =>
    LLMClient.generate(
-      LLMRequest.update(request, {
+      LLM.updateRequest(request, {
        model: model.route
          .with({ auth: Auth.bearer("fresh-key"), headers: { authorization: "Bearer stale" } })
          .model({ id: model.id }),
-        http: HttpOptions.make({
+        http: {
          body: { metadata: { source: "test" } },
          headers: { authorization: "Bearer request", "x-custom": "yes" },
          query: { debug: "1" },
-        }),
+        },
      }),
    ).pipe(
      Effect.provide(
@@ -550,7 +539,7 @@ describe("OpenAI Chat route", () => {
          prompt_tokens: 5,
          completion_tokens: 2,
          total_tokens: 7,
-          prompt_tokens_details: { cached_tokens: 1, cache_write_tokens: 2 },
+          prompt_tokens_details: { cached_tokens: 1 },
          completion_tokens_details: { reasoning_tokens: 0 },
        }),
      )
@@ -558,9 +547,8 @@ describe("OpenAI Chat route", () => {
      const usage = new Usage({
        inputTokens: 5,
        outputTokens: 2,
-        nonCachedInputTokens: 2,
+        nonCachedInputTokens: 4,
        cacheReadInputTokens: 1,
        cacheWriteInputTokens: 2,
        reasoningTokens: 0,
        totalTokens: 7,
        providerMetadata: {
@@ -568,7 +556,7 @@ describe("OpenAI Chat route", () => {
            prompt_tokens: 5,
            completion_tokens: 2,
            total_tokens: 7,
-            prompt_tokens_details: { cached_tokens: 1, cache_write_tokens: 2 },
+            prompt_tokens_details: { cached_tokens: 1 },
            completion_tokens_details: { reasoning_tokens: 0 },
          },
        },
@@ -581,16 +569,10 @@ describe("OpenAI Chat route", () => {
        { type: "text-delta", id: "text-0", text: "Hello" },
        { type: "text-delta", id: "text-0", text: "!" },
        { type: "text-end", id: "text-0" },
-        {
+        { type: "step-finish", index: 0, reason: "stop", usage, providerMetadata: undefined },
          type: "step-finish",
          index: 0,
          reason: { normalized: "stop", raw: "stop" },
          usage,
          providerMetadata: undefined,
        },
        {
          type: "finish",
-          reason: { normalized: "stop", raw: "stop" },
+          reason: "stop",
          usage,
        },
      ])
@@ -630,7 +612,7 @@ describe("OpenAI Chat route", () => {
  it.effect("parses and replays a configured custom reasoning field", () =>
    Effect.gen(function* () {
      const custom = Model.update(model, { compatibility: { reasoningField: "vendor_reasoning" } })
-      const response = yield* LLMClient.generate(LLMRequest.update(request, { model: custom })).pipe(
+      const response = yield* LLMClient.generate(LLM.updateRequest(request, { model: custom })).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
@@ -650,7 +632,9 @@ describe("OpenAI Chat route", () => {
      const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
        LLM.request({ model: custom, messages: [response.message] }),
      )
-      expect(replay.body.messages).toEqual([{ role: "assistant", content: "Hello", vendor_reasoning: "thinking" }])
+      expect(replay.body.messages).toEqual([
        { role: "assistant", content: "Hello", vendor_reasoning: "thinking" },
      ])
    }),
  )
@@ -661,8 +645,8 @@ describe("OpenAI Chat route", () => {
        { type: "reasoning.encrypted", data: "opaque", format: "anthropic-claude-v1", index: 1 },
      ]
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(
        Effect.provide(
@@ -1034,8 +1018,8 @@ describe("OpenAI Chat route", () => {
        deltaChunk({}, "tool_calls"),
      )
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
@@ -1053,14 +1037,8 @@ describe("OpenAI Chat route", () => {
          providerExecuted: undefined,
          providerMetadata: undefined,
        },
-        {
+        { type: "step-finish", index: 0, reason: "tool-calls", usage: undefined, providerMetadata: undefined },
-          type: "step-finish",
+        { type: "finish", reason: "tool-calls", usage: undefined },
          index: 0,
          reason: { normalized: "tool-calls", raw: "tool_calls" },
          usage: undefined,
          providerMetadata: undefined,
        },
        { type: "finish", reason: { normalized: "tool-calls", raw: "tool_calls" }, usage: undefined },
      ])
    }),
  )
@@ -1077,8 +1055,8 @@ describe("OpenAI Chat route", () => {
        deltaChunk({}, "tool_calls"),
      )
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
@@ -1099,8 +1077,8 @@ describe("OpenAI Chat route", () => {
        deltaChunk({}, "tool_calls"),
      )
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
@@ -1117,8 +1095,8 @@ describe("OpenAI Chat route", () => {
        deltaChunk({}, "tool_calls"),
      )
      const error = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedResponse(body)), Effect.flip)
@@ -1135,8 +1113,8 @@ describe("OpenAI Chat route", () => {
        }),
        deltaChunk({ tool_calls: [{ index: 0, function: { arguments: ':"weather"}' } }] }),
      )
-      const input = LLMRequest.update(request, {
+      const input = LLM.updateRequest(request, {
-        tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+        tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
      })
      const events: LLMEvent[] = []
      const streamError = yield* LLMClient.stream(input).pipe(
@@ -1,7 +1,7 @@
 import { describe, expect } from "bun:test"
 import { Effect, Schema } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
-import { LLM, LLMRequest, Message, ToolCallPart, ToolChoice, ToolDefinition } from "../../src"
+import { LLM, Message, ToolCallPart } from "../../src"
 import { Auth, LLMClient } from "../../src/route"
 import * as OpenAICompatible from "../../src/providers/openai-compatible"
 import * as OpenAICompatibleChat from "../../src/protocols/openai-compatible-chat"
@@ -53,9 +53,9 @@ describe("OpenAI-compatible Chat route", () => {
  it.effect("prepares generic Chat target", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
-          toolChoice: ToolChoice.make({ type: "required" }),
+          toolChoice: { type: "required" },
        }),
      )
@@ -232,10 +232,7 @@ describe("OpenAI-compatible Chat route", () => {
      expect(response.text).toBe("Hello!")
      expect(response.usage).toMatchObject({ inputTokens: 5, outputTokens: 2, totalTokens: 7 })
-      expect(response.events.at(-1)).toMatchObject({
+      expect(response.events.at(-1)).toMatchObject({ type: "finish", reason: "stop" })
        type: "finish",
        reason: { normalized: "stop", raw: "stop" },
      })
    }),
  )
 })
@@ -1,22 +1,17 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { LLM, LLMEvent, Message } from "../../src"
+import { LLM } from "../../src"
 import { configure } from "../../src/providers/openai-compatible-responses"
 import { OpenAI } from "../../src/providers"
 import { OpenResponses } from "../../src/protocols/open-responses"
 import { OpenAICompatibleResponses } from "../../src/protocols/openai-compatible-responses"
 import { OpenAIResponses } from "../../src/protocols/openai-responses"
 import { LLMClient } from "../../src/route"
 import { it } from "../lib/effect"
 import { fixedResponse } from "../lib/http"
 import { sseEvents } from "../lib/sse"
-describe("Open Responses-compatible route", () => {
+describe("OpenAI-compatible Responses route", () => {
-  it.effect("uses the Open Responses baseline for a configured deployment", () =>
+  it.effect("reuses the OpenAI Responses protocol for a configured deployment", () =>
    Effect.gen(function* () {
-      expect(OpenAICompatibleResponses.route.body).toBe(OpenResponses.protocol.body)
+      expect(OpenAICompatibleResponses.route.body).toBe(OpenAIResponses.protocol.body)
-      expect(OpenAICompatibleResponses.route.transport).toBe(OpenResponses.httpTransport)
+      expect(OpenAICompatibleResponses.route.transport).toBe(OpenAIResponses.httpTransport)
      expect(OpenAICompatibleResponses.route.body).not.toBe(OpenAIResponses.protocol.body)
      const model = configure({
        apiKey: "test-key",
@@ -32,7 +27,7 @@ describe("Open Responses-compatible route", () => {
      )
      expect(prepared.route).toBe("openai-compatible-responses")
-      expect(prepared.protocol).toBe("open-responses")
+      expect(prepared.protocol).toBe("openai-responses")
      expect(prepared.model).toMatchObject({
        id: "example-model",
        provider: "example",
@@ -50,92 +45,9 @@ describe("Open Responses-compatible route", () => {
          { role: "system", content: "You are concise." },
          { role: "user", content: [{ type: "input_text", text: "Say hello." }] },
        ],
        store: false,
        stream: true,
      })
    }),
  )
  it.effect("rejects OpenAI-native tools", () =>
    Effect.gen(function* () {
      const model = configure({
        apiKey: "test-key",
        baseURL: "https://responses.example.test/v1",
      }).model("example-model")
      const error = yield* LLMClient.prepare(
        LLM.request({ model, prompt: "Draw.", tools: [OpenAI.imageGeneration()] }),
      ).pipe(Effect.flip)
      expect(error.reason._tag).toBe("InvalidRequest")
      expect(error.message).toContain("Open Responses does not support provider-native tool image_generation")
    }),
  )
  it.effect("omits OpenAI-only nullable phases from the Open Responses baseline", () =>
    Effect.gen(function* () {
      const model = configure({
        apiKey: "test-key",
        baseURL: "https://responses.example.test/v1",
      }).model("example-model")
      const prepared = yield* LLMClient.prepare(
        LLM.request({
          model,
          messages: [
            Message.assistant({
              type: "text",
              text: "Unclassified.",
              providerMetadata: { openresponses: { phase: null } },
            }),
          ],
        }),
      )
      expect(prepared.body).toMatchObject({
        input: [{ role: "assistant", content: [{ type: "output_text", text: "Unclassified." }] }],
      })
    }),
  )
  it.effect("reads standard options from the Open Responses namespace", () =>
    Effect.gen(function* () {
      const model = configure({
        apiKey: "test-key",
        baseURL: "https://responses.example.test/v1",
        providerOptions: { openresponses: { reasoningEffort: "low", store: true } },
      }).model("example-model")
      const prepared = yield* LLMClient.prepare(LLM.request({ model, prompt: "Think." }))
      expect(prepared.body).toMatchObject({
        reasoning: { effort: "low" },
        store: true,
      })
    }),
  )
  it.effect("does not interpret OpenAI hosted-tool items", () =>
    Effect.gen(function* () {
      const model = configure({
        apiKey: "test-key",
        baseURL: "https://responses.example.test/v1",
        provider: "example",
      }).model("example-model")
      const response = yield* LLMClient.generate(LLM.request({ model, prompt: "Search." })).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              {
                type: "response.output_item.done",
                item: { type: "web_search_call", id: "ws_1", status: "completed", action: { query: "news" } },
              },
              { type: "response.completed", response: { id: "resp_1" } },
            ),
          ),
        ),
      )
      expect(response.toolCalls).toEqual([])
      expect(response.events.find(LLMEvent.is.finish)).toMatchObject({
        providerMetadata: { openresponses: { responseId: "resp_1" } },
      })
    }),
  )
 })
@@ -1,18 +1,7 @@
 import { describe, expect } from "bun:test"
 import { ConfigProvider, Effect, Layer, Stream } from "effect"
 import { Headers, HttpClientRequest } from "effect/unstable/http"
-import {
+import { LLM, LLMError, LLMEvent, Message, Model, ToolCallPart, ToolResultPart, Usage } from "../../src"
  LLM,
  LLMError,
  LLMEvent,
  LLMRequest,
  Message,
  Model,
  ToolCallPart,
  ToolDefinition,
  ToolResultPart,
  Usage,
 } from "../../src"
 import { Auth, LLMClient, RequestExecutor, WebSocketExecutor } from "../../src/route"
 import * as Azure from "../../src/providers/azure"
 import * as OpenAI from "../../src/providers/openai"
@@ -107,7 +96,7 @@ describe("OpenAI Responses route", () => {
  it.effect("lowers semantic service tier options", () =>
    Effect.gen(function* () {
-      const input = LLMRequest.update(request, { providerOptions: { openai: { serviceTier: "priority" } } })
+      const input = LLM.updateRequest(request, { providerOptions: { openai: { serviceTier: "priority" } } })
      expect(input.providerOptions).toEqual({ openai: { serviceTier: "priority" } })
      const prepared = yield* LLMClient.prepare(input)
@@ -119,7 +108,7 @@ describe("OpenAI Responses route", () => {
  it.effect("passes through custom OpenAI reasoning effort strings", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
-        LLMRequest.update(request, { providerOptions: { openai: { reasoningEffort: "experimental" } } }),
+        LLM.updateRequest(request, { providerOptions: { openai: { reasoningEffort: "experimental" } } }),
      )
      expect(prepared.body.reasoning).toEqual({ effort: "experimental" })
@@ -129,7 +118,7 @@ describe("OpenAI Responses route", () => {
  it.effect("omits unsupported semantic service tiers", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare(
-        LLMRequest.update(request, { providerOptions: { openai: { serviceTier: "unsupported" } } }),
+        LLM.updateRequest(request, { providerOptions: { openai: { serviceTier: "unsupported" } } }),
      )
      expect(prepared.body).not.toHaveProperty("service_tier")
@@ -139,9 +128,9 @@ describe("OpenAI Responses route", () => {
  it.effect("flattens top-level object unions in function schemas", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
          tools: [
-            ToolDefinition.make({
+            {
              name: "read",
              description: "Read a path or resource.",
              inputSchema: {
@@ -163,7 +152,7 @@ describe("OpenAI Responses route", () => {
                  },
                ],
              },
-            }),
+            },
          ],
        }),
      )
@@ -218,7 +207,7 @@ describe("OpenAI Responses route", () => {
  it.effect("prepares OpenAI Responses WebSocket target", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
          model: OpenAIResponses.webSocketRoute
            .with({ endpoint: { baseURL: "https://api.openai.test/v1/" }, auth: Auth.bearer("test") })
            .model({ id: "gpt-4.1-mini" }),
@@ -302,7 +291,7 @@ describe("OpenAI Responses route", () => {
  it.effect("adds native query params to the Responses URL", () =>
    Effect.gen(function* () {
      yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
          model: Model.update(model, { route: model.route.with({ endpoint: { query: { "api-version": "v1" } } }) }),
        }),
      ).pipe(
@@ -324,7 +313,7 @@ describe("OpenAI Responses route", () => {
  it.effect("uses Azure api-key header for static OpenAI Responses keys", () =>
    Effect.gen(function* () {
      yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
          model: Azure.configure({
            baseURL: "https://opencode-test.openai.azure.com/openai/v1/",
            apiKey: "azure-key",
@@ -351,7 +340,7 @@ describe("OpenAI Responses route", () => {
  it.effect("loads OpenAI default auth from Effect Config", () =>
    LLMClient.generate(
-      LLMRequest.update(request, {
+      LLM.updateRequest(request, {
        model: OpenAI.configure({ baseURL: "https://api.openai.test/v1/" }).responses("gpt-4.1-mini"),
      }),
    ).pipe(
@@ -372,7 +361,7 @@ describe("OpenAI Responses route", () => {
  it.effect("lets explicit auth override OpenAI default API key auth", () =>
    LLMClient.generate(
-      LLMRequest.update(request, {
+      LLM.updateRequest(request, {
        model: OpenAI.configure({
          baseURL: "https://api.openai.test/v1/",
          auth: Auth.bearer("oauth-token"),
@@ -832,7 +821,7 @@ describe("OpenAI Responses route", () => {
              input_tokens: 5,
              output_tokens: 2,
              total_tokens: 7,
-              input_tokens_details: { cached_tokens: 1, cache_write_tokens: 2 },
+              input_tokens_details: { cached_tokens: 1 },
              output_tokens_details: { reasoning_tokens: 0 },
            },
          },
@@ -842,9 +831,8 @@ describe("OpenAI Responses route", () => {
      const usage = new Usage({
        inputTokens: 5,
        outputTokens: 2,
-        nonCachedInputTokens: 2,
+        nonCachedInputTokens: 4,
        cacheReadInputTokens: 1,
        cacheWriteInputTokens: 2,
        reasoningTokens: 0,
        totalTokens: 7,
        providerMetadata: {
@@ -852,7 +840,7 @@ describe("OpenAI Responses route", () => {
            input_tokens: 5,
            output_tokens: 2,
            total_tokens: 7,
-            input_tokens_details: { cached_tokens: 1, cache_write_tokens: 2 },
+            input_tokens_details: { cached_tokens: 1 },
            output_tokens_details: { reasoning_tokens: 0 },
          },
        },
@@ -868,13 +856,13 @@ describe("OpenAI Responses route", () => {
        {
          type: "step-finish",
          index: 0,
-          reason: { normalized: "stop", raw: undefined },
+          reason: "stop",
          providerMetadata: { openai: { responseId: "resp_1", serviceTier: "default" } },
          usage,
        },
        {
          type: "finish",
-          reason: { normalized: "stop", raw: undefined },
+          reason: "stop",
          providerMetadata: { openai: { responseId: "resp_1", serviceTier: "default" } },
          usage,
        },
@@ -882,121 +870,6 @@ describe("OpenAI Responses route", () => {
    }),
  )
  it.effect("preserves and replays assistant message phases", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(request).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              {
                type: "response.output_item.added",
                item: { type: "message", id: "msg_commentary" },
              },
              { type: "response.output_text.delta", item_id: "msg_commentary", delta: "Checking." },
              { type: "response.output_text.done", item_id: "msg_commentary" },
              {
                type: "response.output_item.done",
                item: { type: "message", id: "msg_commentary", phase: "commentary" },
              },
              {
                type: "response.output_item.added",
                item: { type: "message", id: "msg_final", phase: "final_answer" },
              },
              { type: "response.output_text.done", item_id: "msg_final", text: "Finished." },
              {
                type: "response.output_item.done",
                item: { type: "message", id: "msg_final", phase: "final_answer" },
              },
              { type: "response.output_item.added", item: { type: "message", id: "msg_null", phase: null } },
              { type: "response.output_text.delta", item_id: "msg_null", delta: "Unclassified." },
              { type: "response.output_item.done", item: { type: "message", id: "msg_null", phase: null } },
              { type: "response.completed", response: { id: "resp_1" } },
            ),
          ),
        ),
      )
      expect(response.message.content).toEqual([
        {
          type: "text",
          text: "Checking.",
          providerMetadata: { openai: { phase: "commentary" } },
        },
        {
          type: "text",
          text: "Finished.",
          providerMetadata: { openai: { phase: "final_answer" } },
        },
        {
          type: "text",
          text: "Unclassified.",
          providerMetadata: { openai: { phase: null } },
        },
      ])
      const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
        LLM.request({ model, messages: [response.message] }),
      )
      expect(prepared.body.input).toEqual([
        {
          role: "assistant",
          content: [{ type: "output_text", text: "Checking." }],
          phase: "commentary",
        },
        {
          role: "assistant",
          content: [{ type: "output_text", text: "Finished." }],
          phase: "final_answer",
        },
        {
          role: "assistant",
          content: [{ type: "output_text", text: "Unclassified." }],
          phase: null,
        },
      ])
    }),
  )
  it.effect("rejects output text events without the spec-required item id", () =>
    Effect.gen(function* () {
      const error = yield* LLMClient.generate(request).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents(
              { type: "response.output_text.delta", delta: "orphaned" },
              { type: "response.completed", response: { id: "resp_1" } },
            ),
          ),
        ),
        Effect.flip,
      )
      expect(error.reason._tag).toBe("InvalidProviderOutput")
      expect(error.message).toContain("response.output_text.delta is missing item_id")
    }),
  )
  it.effect("rejects reasoning events without the spec-required item id", () =>
    Effect.gen(function* () {
      const events = [
        { type: "response.reasoning_summary_part.added", summary_index: 0 },
        { type: "response.reasoning_summary_part.done", summary_index: 0 },
        { type: "response.reasoning_text.done" },
      ]
      for (const event of events) {
        const error = yield* LLMClient.generate(request).pipe(
          Effect.provide(
            fixedResponse(sseEvents(event, { type: "response.completed", response: { id: "resp_1" } })),
          ),
          Effect.flip,
        )
        expect(error.reason._tag).toBe("InvalidProviderOutput")
        expect(error.message).toContain(`${event.type} is missing item_id`)
      }
    }),
  )
  it.effect("maps incomplete response reasons", () =>
    Effect.gen(function* () {
      const generate = (incompleteDetails: object) =>
@@ -1014,13 +887,11 @@ describe("OpenAI Responses route", () => {
      const length = yield* generate({ reason: "max_output_tokens" })
      const contentFilter = yield* generate({ reason: "content_filter" })
      const unknown = yield* generate({})
      const custom = yield* generate({ reason: "provider_limit" })
-      expect([length.finishReason, contentFilter.finishReason, unknown.finishReason, custom.finishReason]).toEqual([
+      expect([length.finishReason, contentFilter.finishReason, unknown.finishReason]).toEqual([
-        { normalized: "length", raw: "max_output_tokens" },
+        "length",
-        { normalized: "content-filter", raw: "content_filter" },
+        "content-filter",
-        { normalized: "unknown", raw: undefined },
+        "unknown",
        { normalized: "unknown", raw: "provider_limit" },
      ])
    }),
  )
@@ -1075,8 +946,8 @@ describe("OpenAI Responses route", () => {
        { type: "text-delta", id: "msg_1", text: "Hello" },
        { type: "reasoning-end", id: "rs_1" },
        { type: "text-end", id: "msg_1" },
-        { type: "step-finish", index: 0, reason: { normalized: "stop", raw: undefined } },
+        { type: "step-finish", index: 0, reason: "stop" },
-        { type: "finish", reason: { normalized: "stop", raw: undefined } },
+        { type: "finish", reason: "stop" },
      ])
      expect(response.events.filter((event) => event.type === "finish")).toHaveLength(1)
      expect(response.message.content).toEqual([
@@ -1121,7 +992,7 @@ describe("OpenAI Responses route", () => {
  it.effect("streams each reasoning summary part as a separate block", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, { providerOptions: { openai: { store: false } } }),
+        LLM.updateRequest(request, { providerOptions: { openai: { store: false } } }),
      ).pipe(
        Effect.provide(
          fixedResponse(
@@ -1167,8 +1038,8 @@ describe("OpenAI Responses route", () => {
          id: "rs_1:1",
          providerMetadata: { openai: { itemId: "rs_1", reasoningEncryptedContent: "encrypted-state" } },
        },
-        { type: "step-finish", index: 0, reason: { normalized: "stop", raw: undefined } },
+        { type: "step-finish", index: 0, reason: "stop" },
-        { type: "finish", reason: { normalized: "stop", raw: undefined } },
+        { type: "finish", reason: "stop" },
      ])
    }),
  )
@@ -1176,7 +1047,7 @@ describe("OpenAI Responses route", () => {
  it.effect("closes reasoning summary parts when storage is not disabled", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, { providerOptions: { openai: { store: true } } }),
+        LLM.updateRequest(request, { providerOptions: { openai: { store: true } } }),
      ).pipe(
        Effect.provide(
          fixedResponse(
@@ -1503,8 +1374,8 @@ describe("OpenAI Responses route", () => {
        { type: "response.completed", response: { usage: { input_tokens: 5, output_tokens: 1 } } },
      )
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
      const usage = new Usage({
@@ -1551,16 +1422,10 @@ describe("OpenAI Responses route", () => {
          providerExecuted: undefined,
          providerMetadata: { openai: { itemId: "item_1" } },
        },
-        {
+        { type: "step-finish", index: 0, reason: "tool-calls", usage, providerMetadata: undefined },
          type: "step-finish",
          index: 0,
          reason: { normalized: "tool-calls", raw: undefined },
          usage,
          providerMetadata: undefined,
        },
        {
          type: "finish",
-          reason: { normalized: "tool-calls", raw: undefined },
+          reason: "tool-calls",
          providerMetadata: undefined,
          usage,
        },
@@ -1589,8 +1454,8 @@ describe("OpenAI Responses route", () => {
        { type: "response.completed", response: { usage: { input_tokens: 5, output_tokens: 1 } } },
      )
      const response = yield* LLMClient.generate(
-        LLMRequest.update(request, {
+        LLM.updateRequest(request, {
-          tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
        }),
      ).pipe(Effect.provide(fixedResponse(body)))
@@ -1600,7 +1465,7 @@ describe("OpenAI Responses route", () => {
        name: "lookup",
        raw: '{"query":"partial',
      })
-      expect(response.finishReason.normalized).toBe("tool-calls")
+      expect(response.finishReason).toBe("tool-calls")
      expect(response.events.some(LLMEvent.is.toolCall)).toBeFalse()
    }),
  )
@@ -1627,7 +1492,7 @@ describe("OpenAI Responses route", () => {
        name: "lookup",
        raw: '{"query":"partial',
      })
-      expect(response.finishReason.normalized).toBe("tool-calls")
+      expect(response.finishReason).toBe("tool-calls")
    }),
  )
@@ -4,8 +4,6 @@ import { LLM, Message } from "../../src"
 import { LLMClient } from "../../src/route"
 import * as OpenRouter from "../../src/providers/openrouter"
 import { it } from "../lib/effect"
 import { fixedResponse } from "../lib/http"
 import { sseEvents } from "../lib/sse"
 describe("OpenRouter", () => {
  it.effect("prepares OpenRouter models through the OpenAI-compatible Chat route", () =>
@@ -56,42 +54,6 @@ describe("OpenRouter", () => {
    }),
  )
  it.effect("preserves the upstream provider finish reason", () =>
    Effect.gen(function* () {
      const model = OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6")
      const response = yield* LLMClient.generate(LLM.request({ model, prompt: "Say hello." })).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents({
              choices: [{ delta: { content: "Hello" }, finish_reason: "stop", native_finish_reason: "end_turn" }],
            }),
          ),
        ),
      )
      expect(response.finishReason).toEqual({ normalized: "stop", raw: "end_turn" })
    }),
  )
  it.effect("fails on a mid-stream provider error", () =>
    Effect.gen(function* () {
      const model = OpenRouter.configure({ apiKey: "test-key" }).model("openai/gpt-4o-mini")
      const error = yield* LLMClient.generate(LLM.request({ model, prompt: "Say hello." })).pipe(
        Effect.provide(
          fixedResponse(
            sseEvents({
              error: { code: 502, message: "Provider disconnected" },
            }),
          ),
        ),
        Effect.flip,
      )
      expect(error.reason).toMatchObject({ _tag: "ProviderInternal" })
      expect(error.message).toContain("Provider disconnected")
    }),
  )
  it.effect("preserves manually supplied reasoning details", () =>
    Effect.gen(function* () {
      const details = [
@@ -106,7 +106,7 @@ const readPdfRuntime = Tool.make({
 })
 const expectCode = (response: LLMResponse) => {
-  expect(response.finishReason.normalized).toBe("stop")
+  expect(response.finishReason).toBe("stop")
  expect(response.text.toUpperCase()).toContain(CODE)
 }
@@ -166,7 +166,7 @@ describe("PDF recorded", () => {
              tools: { read_pdf: readPdfRuntime },
            }).pipe(Stream.runCollect),
          )
-          expect(events.at(-1)).toMatchObject({ type: "finish", reason: { normalized: "stop" } })
+          expect(events.at(-1)).toMatchObject({ type: "finish", reason: "stop" })
          expect(LLMResponse.text({ events }).toUpperCase()).toContain(CODE)
          return
        }
@@ -3,7 +3,6 @@ import { Effect, Schema } from "effect"
 import {
  LLM,
  LLMEvent,
  LLMRequest,
  LLMResponse,
  Message,
  ToolRuntime,
@@ -12,6 +11,7 @@ import {
  toDefinitions,
  type ContentPart,
  type FinishReason,
  type LLMRequest,
  type Model,
 } from "../src"
 import { LLMClient } from "../src/route"
@@ -91,7 +91,7 @@ const restroomImage = () =>
 export const runWeatherToolLoop = (request: LLMRequest) =>
  Effect.gen(function* () {
    const tools = { [weatherToolName]: weatherRuntimeTool }
-    let next = LLMRequest.update(request, { tools: toDefinitions(tools) })
+    let next = LLM.updateRequest(request, { tools: toDefinitions(tools) })
    const events: LLMEvent[] = []
    for (let step = 0; step < 10; step++) {
@@ -108,7 +108,7 @@ export const runWeatherToolLoop = (request: LLMRequest) =>
        ToolRuntime.dispatch(tools, call).pipe(Effect.map((result) => [call, result] as const)),
      )
      events.push(...dispatched.flatMap(([, result]) => result.events))
-      next = LLMRequest.update(next, {
+      next = LLM.updateRequest(next, {
        messages: [
          ...next.messages,
          Message.assistant(assistantContent(response.events)),
@@ -123,8 +123,10 @@ export const runWeatherToolLoop = (request: LLMRequest) =>
 const assistantContent = (events: ReadonlyArray<LLMEvent>) =>
  events.reduce(LLMResponse.reduce, LLMResponse.empty()).message.content
-export const expectFinish = (events: ReadonlyArray<LLMEvent>, reason: FinishReason) =>
+export const expectFinish = (
-  expect(events.at(-1)).toMatchObject({ type: "finish", reason: { normalized: reason } })
+  events: ReadonlyArray<LLMEvent>,
  reason: Extract<LLMEvent, { readonly type: "finish" }>["reason"],
 ) => expect(events.at(-1)).toMatchObject({ type: "finish", reason })
 export const expectWeatherToolCall = (response: LLMResponse) =>
  expect(response.toolCalls).toMatchObject([
@@ -134,10 +136,10 @@ export const expectWeatherToolCall = (response: LLMResponse) =>
 export const expectWeatherToolLoop = (events: ReadonlyArray<LLMEvent>) => {
  const finishes = events.filter(LLMEvent.is.finish)
  expect(finishes).toHaveLength(1)
-  expect(finishes[0]?.reason.normalized).toBe("stop")
+  expect(finishes[0]?.reason).toBe("stop")
  const stepFinishes = events.filter(LLMEvent.is.stepFinish)
-  expect(stepFinishes.map((event) => event.reason.normalized)).toEqual(["tool-calls", "stop"])
+  expect(stepFinishes.map((event) => event.reason)).toEqual(["tool-calls", "stop"])
  const toolCalls = events.filter(LLMEvent.is.toolCall)
  expect(toolCalls).toHaveLength(1)
@@ -501,7 +503,7 @@ export const eventSummary = (events: ReadonlyArray<LLMEvent>) => {
      continue
    }
    if (event.type === "finish") {
-      summary.push({ type: "finish", reason: event.reason.normalized, usage: usageSummary(event.usage) })
+      summary.push({ type: "finish", reason: event.reason, usage: usageSummary(event.usage) })
    }
  }
  return summary.map((item) => Object.fromEntries(Object.entries(item).filter((entry) => entry[1] !== undefined)))
@@ -14,11 +14,11 @@ describe("LLMResponse reducer", () => {
      LLMEvent.reasoningEnd({ id: "r1", providerMetadata: { anthropic: { signature: "sig" } } }),
      LLMEvent.textDelta({ id: "t1", text: "Answer" }),
      LLMEvent.textEnd({ id: "t1" }),
-      LLMEvent.finish({ reason: { normalized: "stop" }, usage: { outputTokens: 5 } }),
+      LLMEvent.finish({ reason: "stop", usage: { outputTokens: 5 } }),
    ]
    const response = LLMResponse.fromEvents(events)
-    expect(response?.finishReason).toEqual({ normalized: "stop" })
+    expect(response?.finishReason).toBe("stop")
    expect(response?.usage).toMatchObject({ outputTokens: 5 })
    expect(response?.events).toEqual(events)
    expect(response?.events.map((event) => event.type)).toEqual([
@@ -62,26 +62,18 @@ describe("LLMResponse reducer", () => {
  test("uses terminal usage when present and keeps prior usage when finish omits it", () => {
    const withFinishUsage = LLMResponse.fromEvents([
-      LLMEvent.stepFinish({ index: 0, reason: { normalized: "stop" }, usage: { inputTokens: 3 } }),
+      LLMEvent.stepFinish({ index: 0, reason: "stop", usage: { inputTokens: 3 } }),
-      LLMEvent.finish({ reason: { normalized: "stop" }, usage: { outputTokens: 2 } }),
+      LLMEvent.finish({ reason: "stop", usage: { outputTokens: 2 } }),
    ])
    const withoutFinishUsage = LLMResponse.fromEvents([
-      LLMEvent.stepFinish({ index: 0, reason: { normalized: "stop" }, usage: { inputTokens: 3 } }),
+      LLMEvent.stepFinish({ index: 0, reason: "stop", usage: { inputTokens: 3 } }),
-      LLMEvent.finish({ reason: { normalized: "stop" } }),
+      LLMEvent.finish({ reason: "stop" }),
    ])
    expect(withFinishUsage?.usage).toMatchObject({ outputTokens: 2 })
    expect(withoutFinishUsage?.usage).toMatchObject({ inputTokens: 3 })
  })
  test("preserves the raw finish reason", () => {
    const response = LLMResponse.fromEvents([
      LLMEvent.finish({ reason: { normalized: "unknown", raw: "provider_limit" } }),
    ])
    expect(response?.finishReason).toEqual({ normalized: "unknown", raw: "provider_limit" })
  })
  test("assembles tool-call content only after the completed tool call event", () => {
    const pending = reduce([
      LLMEvent.toolInputStart({ id: "call_1", name: "lookup" }),
@@ -96,7 +88,7 @@ describe("LLMResponse reducer", () => {
      LLMEvent.toolInputDelta({ id: "call_1", name: "lookup", text: ':"weather"}' }),
      LLMEvent.toolInputEnd({ id: "call_1", name: "lookup" }),
      LLMEvent.toolCall({ id: "call_1", name: "lookup", input: { query: "weather" } }),
-      LLMEvent.finish({ reason: { normalized: "tool-calls" } }),
+      LLMEvent.finish({ reason: "tool-calls" }),
    ])
    expect(response?.message.content).toEqual([
@@ -48,12 +48,8 @@ describe("llm schema", () => {
  })
  test("finish constructors accept usage input", () => {
-    expect(
+    expect(LLMEvent.stepFinish({ index: 0, reason: "stop", usage: { inputTokens: 1 } }).usage).toBeInstanceOf(Usage)
-      LLMEvent.stepFinish({ index: 0, reason: { normalized: "stop" }, usage: { inputTokens: 1 } }).usage,
+    expect(LLMEvent.finish({ reason: "stop", usage: { outputTokens: 2 } }).usage).toBeInstanceOf(Usage)
    ).toBeInstanceOf(Usage)
    expect(LLMEvent.finish({ reason: { normalized: "stop" }, usage: { outputTokens: 2 } }).usage).toBeInstanceOf(
      Usage,
    )
  })
  test("content part tagged union exposes guards", () => {
@@ -1,5 +1,4 @@
 import { describe, expect } from "bun:test"
 import { Content } from "@opencode-ai/schema/tool"
 import { Effect, Schema, Stream } from "effect"
 import {
  GenerationOptions,
@@ -8,6 +7,7 @@ import {
  LLMRequest,
  LLMResponse,
  ToolChoice,
  ToolContent,
  ToolOutput,
  toDefinitions,
 } from "../src"
@@ -279,7 +279,7 @@ describe("LLMClient tools", () => {
  it.effect("models canonical tool files with URIs", () =>
    Effect.sync(() => {
-      const decode = Schema.decodeUnknownSync(Content)
+      const decode = Schema.decodeUnknownSync(ToolContent)
      expect(decode({ type: "file", uri: "data:image/png;base64,AAAA", mime: "image/png" })).toEqual({
        type: "file",
@@ -539,7 +539,6 @@ describe("LLMClient tools", () => {
                  },
                  { type: "content_block_stop", index: 1 },
                  { type: "message_delta", delta: { stop_reason: "tool_use" }, usage: { output_tokens: 5 } },
                  { type: "message_stop" },
                )
              : sseEvents(
                  { type: "message_start", message: { usage: { input_tokens: 5 } } },
@@ -547,7 +546,6 @@ describe("LLMClient tools", () => {
                  { type: "content_block_delta", index: 0, delta: { type: "text_delta", text: "Done." } },
                  { type: "content_block_stop", index: 0 },
                  { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
                  { type: "message_stop" },
                ),
            { headers: { "content-type": "text/event-stream" } },
          )
@@ -555,7 +553,7 @@ describe("LLMClient tools", () => {
      )
      yield* TestToolRuntime.runTools({
-        request: LLMRequest.update(baseRequest, {
+        request: LLM.updateRequest(baseRequest, {
          model: AnthropicMessages.route
            .with({ auth: Auth.header("x-api-key", "test") })
            .model({ id: "claude-sonnet-4-5" }),
@@ -803,7 +801,6 @@ describe("LLMClient tools", () => {
              { type: "content_block_delta", index: 2, delta: { type: "text_delta", text: "Done." } },
              { type: "content_block_stop", index: 2 },
              { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 8 } },
              { type: "message_stop" },
            ),
            { headers: { "content-type": "text/event-stream" } },
          )
@@ -811,7 +808,7 @@ describe("LLMClient tools", () => {
      )
      const events = Array.from(
        yield* TestToolRuntime.runTools({
-          request: LLMRequest.update(baseRequest, {
+          request: LLM.updateRequest(baseRequest, {
            model: AnthropicMessages.route
              .with({ auth: Auth.header("x-api-key", "test") })
              .model({ id: "claude-sonnet-4-5" }),
@@ -1,220 +0,0 @@
 # V1 API Migration Checklist
 The app is currently hybrid. In this document, V1 refers to the legacy unprefixed server APIs used by `@opencode-ai/sdk/v2`, despite the SDK package name.
 ## Events
 - [x] Replace `GET /global/event` with `GET /api/event`.
  - `src/context/server-sdk.tsx`
 - [x] Reduce current granular session and message events into the existing app projections.
  - `src/context/server-session-v2-reducer.ts`
  - `src/context/server-session.ts`
 - [ ] Remove transitional session event dependencies: `session.created`, `session.updated`, `session.diff`, `session.status`, `session.idle`, and `session.error`.
  - `src/context/global-sync/event-reducer.ts`
  - `src/context/server-session.ts`
  - `src/context/notification.tsx`
  - `src/pages/session/usage-exceeded-dialogs.tsx`
 - [ ] Remove legacy message event compatibility: `message.updated`, `message.removed`, `message.part.updated`, `message.part.removed`, and `message.part.delta`.
  - `src/context/global-sync/event-reducer.ts`
  - `src/context/server-session.ts`
 - [x] Adapt current permission and question events to the existing request model.
  - `src/context/global-sync/event-reducer.ts`
  - `src/context/permission.tsx`
 - [x] Consume current file watcher events.
  - `src/context/file.tsx`
 - [x] Consume current VCS events.
  - `src/context/global-sync/event-reducer.ts`
  - `src/pages/session.tsx`
 - [x] Consume current `pty.exited` events.
  - `src/context/terminal.tsx`
 - [ ] Migrate LSP and reference events.
  - `src/context/global-sync/event-reducer.ts`
 ## Sessions
 - [x] Replace `GET /session/status` with one server-scoped `GET /api/session/active` snapshot plus V2 execution events.
  - `src/context/server-sync.tsx`
 - [x] Migrate session listing from `GET /session`.
  - `src/context/server-sync.tsx`
  - `src/context/directory-sync.ts`
  - `src/pages/layout.tsx`
 - [x] Migrate the remaining direct session read from `GET /session/:sessionID`.
  - `src/components/titlebar.tsx`
 - [x] Migrate session updates from `PATCH /session/:sessionID`.
  - `src/context/directory-sync.ts`
  - `src/context/layout.tsx`
  - `src/pages/home.tsx`
  - `src/pages/layout.tsx`
  - `src/pages/session/timeline/message-timeline.tsx`
  - `src/components/titlebar-tab-nav.tsx`
  - Renames use `POST /api/session/:sessionID/rename`; archival uses `POST /api/session/:sessionID/archive`.
 - [x] Migrate session deletion from `DELETE /session/:sessionID`.
  - `src/pages/session/timeline/message-timeline.tsx`
 - [x] Remove session diff loading from `GET /session/:sessionID/diff`.
  - Historical Session diffs remain unavailable until the current API defines their snapshot semantics.
 - [x] Migrate abort from `POST /session/:sessionID/abort`.
  - `src/components/prompt-input/submit.ts`
  - `src/pages/session/use-session-commands.tsx`
  - `src/pages/session.tsx`
 - [x] Migrate revert and unrevert from `POST /session/:sessionID/revert` and `POST /session/:sessionID/unrevert`.
  - `src/pages/session/use-session-commands.tsx`
  - `src/pages/session.tsx`
 - [x] Replace `POST /session/:sessionID/summarize` with the current compact API.
  - `src/pages/session/use-session-commands.tsx`
 - [x] Migrate slash commands from `POST /session/:sessionID/command`.
  - `src/components/prompt-input/submit.ts`
 - [x] Migrate shell execution from `POST /session/:sessionID/shell`.
  - `src/components/prompt-input/submit.ts`
 - [x] Migrate session fork from `POST /session/:sessionID/fork`.
  - `src/components/dialog-fork.tsx`
 - [ ] Migrate sharing from `POST /session/:sessionID/share` and `DELETE /session/:sessionID/share`.
  - `src/pages/session/use-session-commands.tsx`
  - `src/pages/session/timeline/message-timeline.tsx`
  - Blocked: the current API has no sharing contract or implementation.
 ## Session Compatibility Fallbacks
 These calls are retained as fallback adapters. The current production path supplies the current session and message APIs.
 - [ ] Remove fallback `GET /session/:sessionID` after compatibility support is unnecessary.
  - `src/context/server-session.ts`
 - [ ] Remove fallback `GET /session/:sessionID/message` after compatibility support is unnecessary.
  - `src/context/server-session.ts`
 - [ ] Remove fallback `GET /session/:sessionID/message/:messageID` after compatibility support is unnecessary.
  - `src/context/server-session.ts`
 ## Filesystem
 - [ ] Migrate file listing from `GET /file`.
  - `src/context/file.tsx`
 - [ ] Migrate file reads from `GET /file/content`.
  - `src/context/file.tsx`
  - `src/pages/session/review-tab.tsx`
  - `src/pages/session/v2/review-panel-v2.tsx`
 - [x] Migrate path discovery from `GET /path` to `GET /api/path`.
  - `src/context/global-sync/bootstrap.ts`
  - `src/components/dialog-select-directory.tsx`
  - `src/components/dialog-select-directory-v2.tsx`
 ## Projects And Worktrees
 - [x] Migrate project listing from `GET /project` to `GET /api/project`.
  - `src/context/global-sync/bootstrap.ts`
 - [x] Migrate the current project lookup from `GET /project/current` to `GET /api/project/current`.
  - `src/context/global-sync/bootstrap.ts`
 - [ ] Migrate Git initialization from `POST /project/git/init`.
  - `src/pages/session.tsx`
 - [x] Migrate project updates from `PATCH /project/:projectID` to `PATCH /api/project/:projectID`.
  - `src/context/layout.tsx`
  - `src/components/edit-project.ts`
  - `src/pages/layout.tsx`
 - [ ] Migrate experimental worktree listing, creation, removal, and reset from `/experimental/worktree`.
  - `src/pages/layout.tsx`
  - `src/components/prompt-input/submit.ts`
  - Listing now uses `GET /api/project/:projectID/directories`; create, removal, and reset remain.
 - [ ] Migrate instance disposal from `POST /instance/dispose`.
  - `src/pages/layout.tsx`
 ## VCS
 - [x] Migrate repository information from `GET /vcs` to `GET /api/vcs`.
  - `src/context/global-sync/bootstrap.ts`
 - [x] Migrate diffs from `GET /vcs/diff` to `GET /api/vcs/diff`.
  - `src/pages/session.tsx`
 - [x] Migrate status from `GET /vcs/status` to `GET /api/vcs/status`.
  - `src/pages/layout.tsx`
 ## Configuration And Authentication
 - [ ] Migrate global configuration reads from `GET /global/config`.
  - `src/context/global-sync/bootstrap.ts`
 - [ ] Migrate directory configuration reads from `GET /config`.
  - `src/context/global-sync/bootstrap.ts`
 - [ ] Migrate global configuration updates from `PATCH /global/config`.
  - `src/context/server-sync.tsx`
 - [x] Migrate provider authentication method discovery from `GET /provider/auth` to `GET /api/integration/:integrationID`.
  - `src/components/dialog-connect-provider.tsx`
 - [x] Migrate built-in provider OAuth authorization and callbacks to `/api/integration/:integrationID/connect/oauth/*`.
  - `src/components/dialog-connect-provider.tsx`
 - [ ] Migrate remaining credentials from `PUT /auth/:providerID` and `DELETE /auth/:providerID`.
  - Built-in provider key connections now use `POST /api/integration/:integrationID/connect/key`.
  - `src/components/dialog-connect-provider.tsx`
  - `src/components/dialog-custom-provider.tsx`
  - `src/components/settings-providers.tsx`
  - `src/components/settings-v2/providers.tsx`
 - [ ] Migrate global disposal from `POST /global/dispose`.
  - `src/components/dialog-connect-provider.tsx`
  - `src/components/settings-providers.tsx`
  - `src/components/settings-v2/providers.tsx`
 ## Permissions And Questions
 - [x] Migrate permission listing from `GET /permission` to `GET /api/permission/request`.
  - `src/context/global-sync/bootstrap.ts`
  - `src/context/permission.tsx`
 - [x] Migrate permission responses from `/session/:sessionID/permissions/:permissionID`.
  - `src/context/permission.tsx`
  - `src/pages/session/composer/session-composer-state.ts`
 - [x] Migrate question listing from `GET /question` to `GET /api/question/request`.
  - `src/context/global-sync/bootstrap.ts`
 - [x] Migrate question replies and rejections from `/question/:requestID/*` to `/api/session/:sessionID/question/:requestID/*`.
  - `src/pages/session/composer/session-question-dock.tsx`
 ## Commands, MCP, LSP, And References
 - [x] Migrate command listing from `GET /command` to `GET /api/command`.
  - `src/context/global-sync/bootstrap.ts`
  - `src/context/server-sync.tsx`
 - [x] Migrate MCP listing, connection, and disconnection from `/mcp` to `/api/mcp`.
  - `src/context/server-sync.tsx`
 - [ ] Replace legacy MCP authentication with the Integration OAuth workflow.
  - `src/context/server-sync.tsx`
 - [x] Migrate experimental resource listing from `GET /experimental/resource` to `GET /api/mcp/resource`.
  - `src/context/server-sync.tsx`
 - [ ] Migrate LSP status from `GET /lsp`.
  - `src/context/server-sync.tsx`
 - [x] Move `GET /api/reference` off the legacy generated SDK transport.
  - `src/context/global-sync/bootstrap.ts`
 ## Search
 - [x] Migrate global session search from `GET /experimental/session` to `GET /api/session`.
  - `src/components/command-palette.ts`
  - `src/components/dialog-command-palette-v2.tsx`
 ## PTY And Terminal
 - [x] Migrate PTY creation, reads, updates, and deletion from `/pty` to `/api/pty`.
  - `src/context/terminal.tsx`
  - `src/components/terminal.tsx`
 - [x] Migrate shell listing from `GET /pty/shells` to `GET /api/pty/shells`.
  - `src/components/settings-general.tsx`
  - `src/components/settings-v2/general.tsx`
 - [x] Migrate connection tokens from `POST /pty/:ptyID/connect-token` to `POST /api/pty/:ptyID/connect-token`.
  - `src/components/terminal.tsx`
 - [x] Migrate the direct WebSocket connection from `/pty/:ptyID/connect` to `/api/pty/:ptyID/connect`.
  - `src/components/terminal.tsx`
 ## Legacy Types And Adapters
 These are not V1 network requests, but they keep the UI coupled to V1 data contracts.
 - [ ] Replace the current-session-to-legacy-session adapter.
  - `src/utils/session.ts`
 - [ ] Replace the current-message-to-legacy-message-and-part adapter.
  - `src/utils/session-message.ts`
 - [ ] Replace current agent, provider, and model adapters to legacy SDK structures.
  - `src/context/global-sync/utils.ts`
 - [ ] Replace legacy `Session`, `Message`, `Part`, `PermissionRequest`, `QuestionRequest`, `Project`, `FileNode`, `FileDiffInfo`, and `Event` types throughout app state and rendering.
 - [ ] Remove the `@opencode-ai/sdk` runtime dependency after all legacy calls and types are gone.
  - `package.json`
 ## Test Infrastructure
 - [ ] Replace V1 endpoint mocks with current API mocks.
  - `e2e/utils/mock-server.ts`
 - [x] Replace `/global/event` and `/event` interception with current event transport handling.
  - `e2e/utils/sse-transport.ts`
 - [ ] Replace `SessionV1` and legacy SDK fixtures in timeline performance tests.
  - `e2e/performance/timeline-stability/fixture.ts`
 - [ ] Remove remaining legacy SDK type fixtures from unit and browser tests.
@@ -20,7 +20,7 @@ const profiles = [
  { name: "edit", tool: "edit", input: { filePath: "src/edit.ts" } },
  {
    name: "multi patch",
-    tool: "apply_patch",
+    tool: "patch",
    input: { files: ["src/a.ts", "src/b.ts", "src/old.ts", "src/moved.ts"] },
  },
 ] as const
@@ -25,7 +25,7 @@ test("adds patch files incrementally without resetting outer expansion", async (
      userMessage(),
      assistantMessage(
        [
-          toolPart(patchID, "apply_patch", "running", { files: [first.filePath] }, { metadata: { files: [first] } }),
+          toolPart(patchID, "patch", "running", { files: [first.filePath] }, { metadata: { files: [first] } }),
          textPart(followingID, "Following incremental patch"),
        ],
        { completed: false },
@@ -49,7 +49,7 @@ test("adds patch files incrementally without resetting outer expansion", async (
    partUpdated(
      toolPart(
        patchID,
-        "apply_patch",
+        "patch",
        "running",
        { files: [first.filePath, second.filePath] },
        { metadata: { files: [first, second] } },
@@ -61,7 +61,7 @@ test("adds patch files incrementally without resetting outer expansion", async (
    partUpdated(
      toolPart(
        patchID,
-        "apply_patch",
+        "patch",
        "completed",
        { files: [first.filePath, second.filePath, third.filePath] },
        { metadata: { files: [first, second, third] } },
@@ -97,7 +97,6 @@ export async function setupTimeline(
    locale?: string
    deviceScaleFactor?: number
    seedHistory?: boolean
    protocol?: "v1" | "v2"
  } = {},
 ) {
  const sessions = input.sessions ?? [session()]
@@ -115,7 +114,6 @@ export async function setupTimeline(
    retry: input.eventRetry ?? 20,
  })
  await mockOpenCodeServer(page, {
    protocol: input.protocol,
    directory,
    project: project(),
    provider: provider(),
@@ -33,11 +33,9 @@ test.describe("timeline tool state stability", () => {
    }
    const names = { webfetch: "webfetch", websearch: "websearch", task: "task", skill: "skill", custom: "mcp_probe" }
    const questionID = "prt_state_question"
    const todoID = "prt_state_todo"
    const initial = [
      ...ids.map((id) => toolPart(`prt_state_${id}`, names[id], "pending", inputs[id])),
      toolPart(questionID, "question", "pending", questionInput()),
      toolPart(todoID, "todowrite", "pending", { todos: [{ content: "Hidden", status: "pending" }] }),
      textPart("prt_state_following", "Following lightweight tools"),
    ]
    const childID = "ses_timeline_child"
@@ -49,7 +47,6 @@ test.describe("timeline tool state stability", () => {
    await timeline.send(status("busy"), 120)
    for (const id of ids) await timeline.waitForPart(`prt_state_${id}`)
    await expect(page.locator(`[data-timeline-part-id="${questionID}"]`)).toHaveCount(0)
    await expect(page.locator(`[data-timeline-part-id="${todoID}"]`)).toHaveCount(0)
    const regionIDs = [
      "prt_state_webfetch",
@@ -105,7 +102,6 @@ test.describe("timeline tool state stability", () => {
      ]),
    )
    await expect(page.locator(`[data-timeline-part-id="${questionID}"]`)).toContainText("Keep it stable")
    await expect(page.locator(`[data-timeline-part-id="${todoID}"]`)).toHaveCount(0)
    await expect(
      page.locator(`a[href$="/session/${childID}"]`, { has: page.locator('[data-component="task-tool-card"]') }),
    ).toBeVisible()
@@ -41,12 +41,7 @@ const assistants = Array.from({ length: 14 }, (_, index) => {
 const messages = [user, ...assistants]
 const target = fixture.sessions.find((session) => session.id === fixture.targetID)!
 const lastID = userID
-const lastAssistant = assistants.at(-1)!
+const lastPartID = assistants.at(-1)!.parts.at(-1)!.id
 const lastPart = lastAssistant.parts.at(-1)!
 const lastPartID =
  lastPart.type === "tool"
    ? lastPart.id
    : `${lastAssistant.info.id}:${lastPart.type}:${lastAssistant.parts.filter((part) => part.type === lastPart.type).length - 1}`
 benchmark("hydrates an orphaned latest turn after a cold session click", async ({ browser, report }, testInfo) => {
  benchmark.setTimeout(180_000)
@@ -112,25 +107,9 @@ async function trial(page: Page, mode: ParentHydrationBenchmarkMode) {
      return { items: items.slice(start, end), cursor: start > 0 ? items[start]!.info.id : undefined }
    },
  })
-  await page.route(`**/session/${fixture.targetID}`, (route) => {
+  await page.route(`**/session/${fixture.targetID}`, (route) =>
-    const current = new URL(route.request().url()).pathname.startsWith("/api/")
+    route.fulfill({ status: 200, contentType: "application/json", body: JSON.stringify(target) }),
-    return route.fulfill({
+  )
      status: 200,
      contentType: "application/json",
      body: JSON.stringify(
        current
          ? {
              data: {
                ...target,
                cost: 0,
                tokens: { input: 0, output: 0, reasoning: 0, cache: { read: 0, write: 0 } },
                location: { directory: target.directory },
              },
            }
          : target,
      ),
    })
  })
  await installStressSessionTabs(page, { sessionIDs: [fixture.sourceID] })
  await page.goto(stressSessionHref(fixture.sourceID))
  await expectSessionTitle(page, fixture.expected.sourceTitle)
@@ -165,8 +144,8 @@ async function trial(page: Page, mode: ParentHydrationBenchmarkMode) {
    parent: requests.filter((request) => request.type === "parent").length,
  }
  if (mode === "candidate") {
-    expect(requestCounts.parent).toBe(0)
+    expect(requestCounts.parent).toBe(1)
-    expect(historyGates).toBe(0)
+    expect(historyGates).toBe(1)
  }
  return { metrics, requestCounts, historyGateCount: historyGates }
 }
@@ -295,7 +295,7 @@ function performanceTurn(index: number) {
            messageID: assistantID,
            type: "tool",
            callID: `call_0000_${suffix}_patch`,
-            tool: "apply_patch",
+            tool: "patch",
            state: {
              status: "completed",
              input: { patchText: realisticPatch(index) },
@@ -131,7 +131,7 @@ function toolPart(
 ): MessagePart {
  const metadata =
    metadataOverride ??
-    (tool === "apply_patch"
+    (tool === "patch"
      ? { files: [patchFile(index, "update"), patchFile(index + 1, index % 2 === 0 ? "add" : "delete")] }
      : tool === "edit" || tool === "write"
        ? {
@@ -219,7 +219,7 @@ function turn(index: number): Message[] {
      ? [toolPart(index, 7, "write", { filePath: `src/generated/write-${index}.ts`, content: code(index, 28) }, 560)]
      : []),
    ...(index % 8 === 0
-      ? [toolPart(index, 8, "apply_patch", { files: [`src/generated/patch-${index}.ts`] }, 620)]
+      ? [toolPart(index, 8, "patch", { files: [`src/generated/patch-${index}.ts`] }, 620)]
      : []),
    ...(index % 7 === 0
      ? [toolPart(index, 4, "bash", { command: "bun typecheck", description: "Verify generated output" }, 620)]
@@ -269,7 +269,6 @@ const childMessages = Array.from({ length: 4 }, (_, index) => [
 ]).flat()
 function renderable(part: MessagePart) {
  if (part.type === "tool" && part.tool === "todowrite") return false
  if (part.type === "text") return !!part.text.trim()
  if (part.type === "reasoning") return !!part.text.trim()
  return part.type !== "step-start" && part.type !== "step-finish" && part.type !== "patch"
@@ -1,6 +1,5 @@
 import { expect, test, type Page, type Route } from "@playwright/test"
 import { base64Encode } from "@opencode-ai/core/util/encode"
 import { currentSession } from "../utils/mock-server"
 const serverA = "http://127.0.0.1:4096"
 const serverB = "http://127.0.0.1:4097"
@@ -34,7 +33,7 @@ test("closing the active server's last tab opens the remaining server tab", asyn
  await tabA.locator('[data-slot="tab-close"] button').click()
  await expect(page).toHaveURL(new RegExp(`${hrefB.replace(/[.*+?^${}()|[\]\\]/g, "\\$&")}$`))
-  await expect.poll(() => requests.some((url) => url.startsWith(`${serverB}/api/session/${sessionB.id}`))).toBe(true)
+  await expect.poll(() => requests.some((url) => url.startsWith(`${serverB}/session/${sessionB.id}`))).toBe(true)
  await expect(page.getByText(sessionB.title).first()).toBeVisible()
  const sessionBRequests = requests.filter((url) => url.includes(`/session/${sessionB.id}`))
  expect(sessionBRequests.every((url) => url.startsWith(serverB))).toBe(true)
@@ -85,21 +84,17 @@ async function mockServers(page: Page, requests: string[]) {
    const current = url.origin === serverA ? sessionA : sessionB
    const directory = url.searchParams.get("directory")
    if (directory && directory !== current.directory) return json(route, { name: "InvalidDirectory" }, 500)
-    if (url.pathname === "/global/event" || url.pathname === "/event" || url.pathname === "/api/event")
+    if (url.pathname === "/global/event" || url.pathname === "/event") return sse(route)
-      return sse(route)
+    if (url.pathname === "/global/health") return json(route, { healthy: true })
-    if (url.pathname === "/global/health") return json(route, {}, 404)
+    if (url.pathname === "/session") return json(route, [current])
    if (url.pathname === "/api/health") return json(route, { pid: 1 })
    if (url.pathname === "/api/session") return json(route, { data: [currentSession(current)], cursor: {} })
    if (url.pathname === "/api/session/active") return json(route, { data: {} })
    if (url.pathname === `/api/session/${current.id}`) return json(route, { data: currentSession(current) })
    if (url.pathname === `/api/session/${current.id}/message`) return json(route, { data: [], cursor: {} })
    if (url.pathname === `/session/${current.id}`) return json(route, current)
    if (/^\/session\/[^/]+$/.test(url.pathname)) return json(route, { name: "NotFoundError" }, 404)
    if (url.pathname === `/session/${current.id}/message`) return json(route, [])
-    if (/^\/session\/[^/]+\/(children|todo|diff)$/.test(url.pathname)) return json(route, [])
+    if (/^\/session\/[^/]+\/(children|diff)$/.test(url.pathname)) return json(route, [])
    if (["/skill", "/command", "/lsp", "/formatter", "/permission", "/question", "/vcs/diff"].includes(url.pathname))
      return json(route, [])
-    if (["/global/config", "/config", "/provider/auth", "/mcp"].includes(url.pathname)) return json(route, {})
+    if (["/global/config", "/config", "/provider/auth", "/mcp", "/session/status"].includes(url.pathname))
      return json(route, {})
    if (url.pathname === "/provider")
      return json(route, { all: [], connected: [], default: { providerID: "", modelID: "" } })
    if (url.pathname === "/agent") return json(route, [{ name: "build", mode: "primary" }])
@@ -121,20 +116,7 @@ async function mockServers(page: Page, requests: string[]) {
        directory: current.directory,
        home: current.directory,
      })
    if (url.pathname === "/api/path")
      return json(route, {
        state: current.directory,
        config: current.directory,
        worktree: current.directory,
        directory: current.directory,
        home: current.directory,
      })
    if (url.pathname === "/vcs") return json(route, { branch: "main", default_branch: "main" })
    if (url.pathname === "/api/vcs")
      return json(route, {
        location: { directory: current.directory },
        data: { branch: "main", defaultBranch: "main" },
      })
    return json(route, {})
  })
 }
@@ -1,132 +0,0 @@
 import { base64Encode } from "@opencode-ai/core/util/encode"
 import { expect, test } from "@playwright/test"
 import { mockOpenCodeServer } from "../utils/mock-server"
 import { expectSessionTitle } from "../utils/waits"
 const directory = "C:/OpenCode/OpenFileExpand"
 const projectID = "proj_open_file_expand"
 const sessionID = "ses_open_file_expand"
 const title = "Open file expand"
 const server = `http://${process.env.PLAYWRIGHT_SERVER_HOST ?? "127.0.0.1"}:${process.env.PLAYWRIGHT_SERVER_PORT ?? "4096"}`
 test.use({ viewport: { width: 1440, height: 900 } })
 test("expands a folder whose path has a trailing Windows separator", async ({ page }) => {
  await mockOpenCodeServer(page, {
    directory,
    project: {
      id: projectID,
      worktree: directory,
      vcs: "git",
      name: "open-file-expand",
      time: { created: 1700000000000, updated: 1700000000000 },
      sandboxes: [],
    },
    provider: {
      all: [
        {
          id: "opencode",
          name: "OpenCode",
          models: { test: { id: "test", name: "Test", limit: { context: 200_000 } } },
        },
      ],
      connected: ["opencode"],
      default: { providerID: "opencode", modelID: "test" },
    },
    sessions: [
      {
        id: sessionID,
        slug: sessionID,
        projectID,
        directory,
        title,
        version: "dev",
        time: { created: 1700000000000, updated: 1700000000000 },
      },
    ],
    vcsDiff: [],
    fileList: (path) => {
      if (path === "frontend\\" || path === "frontend") {
        return [
          {
            name: "app.ts",
            path: "frontend\\app.ts",
            absolute: `${directory}/frontend/app.ts`,
            type: "file" as const,
            ignored: false,
          },
        ]
      }
      if (path) return []
      return [
        {
          name: "frontend",
          path: "frontend\\",
          absolute: `${directory}/frontend`,
          type: "directory" as const,
          ignored: false,
        },
        {
          name: "README.md",
          path: "README.md",
          absolute: `${directory}/README.md`,
          type: "file" as const,
          ignored: false,
        },
      ]
    },
    fileContent: (path) => ({ type: "text", content: `contents:${path}` }),
    pageMessages: () => ({ items: [] }),
  })
  await page.addInitScript(
    ({ directory, server, sessionID }) => {
      localStorage.setItem(
        "settings.v3",
        JSON.stringify({ general: { newLayoutDesigns: true, shouldDisplayTabsToast: false } }),
      )
      localStorage.setItem(
        "opencode.global.dat:server",
        JSON.stringify({
          projects: { local: [{ worktree: directory, expanded: true }] },
          lastProject: { local: directory },
        }),
      )
      localStorage.setItem(
        "opencode.global.dat:layout",
        JSON.stringify({ review: { diffStyle: "split", panelOpened: true } }),
      )
      localStorage.setItem(
        "opencode.global.dat:review-panel-v2",
        JSON.stringify({ sidebarOpened: true, sidebarWidth: 240, expandMode: "collapse" }),
      )
      localStorage.setItem(
        "opencode.window.browser.dat:tabs",
        JSON.stringify([{ type: "session", server, sessionId: sessionID }]),
      )
    },
    { directory, server, sessionID },
  )
  await page.goto(`/server/${base64Encode(server)}/session/${sessionID}`)
  await expectSessionTitle(page, title)
  const panel = page.locator("#review-panel")
  await panel.getByRole("button", { name: "Open file" }).click()
  await expect(panel.getByRole("tab", { name: "Open file" })).toHaveAttribute("data-selected", "")
  const sidebar = panel.locator('[data-component="session-review-v2-sidebar-root"]')
  await expect(sidebar).toBeVisible()
  const frontendRow = panel.locator('[data-slot="file-tree-v2-row"][data-path="frontend"]')
  await expect(frontendRow).toBeVisible()
  await expect(frontendRow).toHaveAttribute("aria-expanded", "false")
  await frontendRow.click()
  await expect(frontendRow).toHaveAttribute("aria-expanded", "true")
  const appRow = panel.locator('[data-slot="file-tree-v2-row"][data-path="frontend/app.ts"]')
  await expect(appRow).toBeVisible()
  await appRow.click()
  await expect(panel.getByRole("tab", { name: "app.ts" })).toHaveAttribute("data-selected", "")
  await expect(panel.getByText("contents:frontend/app.ts", { exact: true })).toBeVisible()
 })
@@ -1,7 +1,6 @@
 import { base64Encode } from "@opencode-ai/core/util/encode"
 import { expect, test, type Page, type Route } from "@playwright/test"
 import { installSseTransport } from "../utils/sse-transport"
 import { currentSession } from "../utils/mock-server"
 const serverA = "http://127.0.0.1:4096"
 const serverB = "http://127.0.0.1:4097"
@@ -18,7 +17,7 @@ test("session settings use the remote server context", async ({ page }) => {
  await page.goto(`/server/${base64Encode(serverB)}/session/${sessionB.id}`)
  await expect(page.getByText(sessionB.title).first()).toBeVisible()
-  await page.keyboard.press("Control+,")
+  await page.keyboard.press(process.platform === "darwin" ? "Meta+," : "Control+,")
  const dialog = page.locator(".settings-v2-dialog")
  const autoAccept = dialog.locator('[data-action="settings-auto-accept-permissions"]')
@@ -59,7 +58,7 @@ test("auto-accept responds for an unfocused server session", async ({ page }) =>
  const hrefB = `/server/${base64Encode(serverB)}/session/${sessionB.id}`
  await page.goto(`/server/${base64Encode(serverA)}/session/${sessionA.id}`)
  await expect(page.getByText(sessionA.title).first()).toBeVisible()
-  await page.keyboard.press("Control+,")
+  await page.keyboard.press(process.platform === "darwin" ? "Meta+," : "Control+,")
  const autoAccept = page.locator(".settings-v2-dialog").locator('[data-action="settings-auto-accept-permissions"]')
  await autoAccept.locator('[data-slot="switch-control"]').click()
  await expect(autoAccept.getByRole("switch")).toBeChecked()
@@ -181,36 +180,10 @@ async function mockServers(page: Page, permissionRequests: string[], permissionR
      return json(route, true)
    }
    if (requestDirectory && requestDirectory !== directory) return json(route, { name: "InvalidDirectory" }, 500)
-    if (url.pathname === "/global/event" || url.pathname === "/event" || url.pathname === "/api/event")
+    if (url.pathname === "/global/event" || url.pathname === "/event") return sse(route)
      return sse(route)
    if (url.pathname === "/global/health") return json(route, { healthy: true })
-    if (url.pathname === "/api/provider" || url.pathname === "/api/model" || url.pathname === "/api/agent")
+    if (url.pathname === "/session/status") return json(route, {})
-      return json(route, { data: [] })
+    if (url.pathname === "/session") return json(route, sessions)
    if (url.pathname === "/api/model/default") return json(route, { data: null })
    if (["/api/command", "/api/reference", "/api/permission/request", "/api/question/request"].includes(url.pathname))
      return json(route, { location: { directory }, data: [] })
    if (url.pathname === "/api/mcp") return json(route, { location: { directory }, data: [] })
    if (url.pathname === "/api/mcp/resource")
      return json(route, { location: { directory }, data: { resources: [], templates: [] } })
    if (url.pathname === "/api/project") {
      return json(route, [
        {
          id: remote ? sessionB.projectID : "project-server-a",
          worktree: directory,
          vcs: "git",
          time: { created: 1, updated: 1 },
          sandboxes: [],
        },
      ])
    }
    if (url.pathname === "/api/project/current")
      return json(route, { id: remote ? sessionB.projectID : "project-server-a", directory })
    if (url.pathname === "/api/session") return json(route, { data: sessions.map(currentSession), cursor: {} })
    if (url.pathname === "/api/session/active") return json(route, { data: {} })
    const currentSessionInfo = sessions.find((session) => url.pathname === `/api/session/${session.id}`)
    if (currentSessionInfo) return json(route, { data: currentSession(currentSessionInfo) })
    if (sessions.some((session) => url.pathname === `/api/session/${session.id}/message`))
      return json(route, { data: [], cursor: {} })
    const current = sessions.find((session) => url.pathname === `/session/${session.id}`)
    if (current) return json(route, current)
    if (/^\/session\/[^/]+$/.test(url.pathname)) return json(route, { name: "NotFoundError" }, 404)
@@ -243,12 +216,7 @@ async function mockServers(page: Page, permissionRequests: string[], permissionR
        directory,
        home: directory,
      })
    if (url.pathname === "/api/path")
      return json(route, { state: directory, config: directory, worktree: directory, directory, home: directory })
    if (url.pathname === "/vcs") return json(route, { branch: "main", default_branch: "main" })
    if (url.pathname === "/api/vcs")
      return json(route, { location: { directory }, data: { branch: "main", defaultBranch: "main" } })
    if (url.pathname === "/api/pty/shells") return json(route, { location: { directory }, data: [] })
    return json(route, {})
  })
 }
@@ -1,6 +1,5 @@
 import { expect, test, type Page, type Route } from "@playwright/test"
 import { base64Encode } from "@opencode-ai/core/util/encode"
 import { currentSession } from "../utils/mock-server"
 const serverA = "http://127.0.0.1:4096"
 const serverB = "http://127.0.0.1:4097"
@@ -58,19 +57,15 @@ async function mockServers(page: Page) {
    const current = url.origin === serverA ? sessionA : sessionB
    const directory = url.searchParams.get("directory")
    if (directory && directory !== current.directory) return json(route, { name: "InvalidDirectory" }, 500)
-    if (url.pathname === "/global/event" || url.pathname === "/event" || url.pathname === "/api/event")
+    if (url.pathname === "/global/event" || url.pathname === "/event") return sse(route)
-      return sse(route, url.pathname === "/api/event")
+    if (url.pathname === "/global/health") return json(route, { healthy: true })
-    if (url.pathname === "/global/health") return json(route, {}, 404)
+    if (url.pathname === "/session/status")
-    if (url.pathname === "/api/health") return json(route, { pid: 1 })
+      return json(route, url.origin === serverB ? { [sessionB.id]: { type: "busy" } } : {})
-    if (url.pathname === "/api/session/active")
+    if (url.pathname === "/session") return json(route, [current])
      return json(route, { data: url.origin === serverB ? { [sessionB.id]: { type: "running" } } : {} })
    if (url.pathname === "/api/session") return json(route, { data: [currentSession(current)], cursor: {} })
    if (url.pathname === `/api/session/${current.id}`) return json(route, { data: currentSession(current) })
    if (url.pathname === `/api/session/${current.id}/message`) return json(route, { data: [], cursor: {} })
    if (url.pathname === `/session/${current.id}`) return json(route, current)
    if (/^\/session\/[^/]+$/.test(url.pathname)) return json(route, { name: "NotFoundError" }, 404)
    if (url.pathname === `/session/${current.id}/message`) return json(route, [])
-    if (/^\/session\/[^/]+\/(children|todo|diff)$/.test(url.pathname)) return json(route, [])
+    if (/^\/session\/[^/]+\/(children|diff)$/.test(url.pathname)) return json(route, [])
    if (["/skill", "/command", "/lsp", "/formatter", "/permission", "/question", "/vcs/diff"].includes(url.pathname))
      return json(route, [])
    if (["/global/config", "/config", "/provider/auth", "/mcp"].includes(url.pathname)) return json(route, {})
@@ -95,20 +90,7 @@ async function mockServers(page: Page) {
        directory: current.directory,
        home: current.directory,
      })
    if (url.pathname === "/api/path")
      return json(route, {
        state: current.directory,
        config: current.directory,
        worktree: current.directory,
        directory: current.directory,
        home: current.directory,
      })
    if (url.pathname === "/vcs") return json(route, { branch: "main", default_branch: "main" })
    if (url.pathname === "/api/vcs")
      return json(route, {
        location: { directory: current.directory },
        data: { branch: "main", defaultBranch: "main" },
      })
    return json(route, {})
  })
 }
@@ -122,10 +104,6 @@ function json(route: Route, body: unknown, status = 200) {
  })
 }
-function sse(route: Route, current: boolean) {
+function sse(route: Route) {
-  return route.fulfill({
+  return route.fulfill({ status: 200, contentType: "text/event-stream", body: ": ok\n\n" })
    status: 200,
    contentType: "text/event-stream",
    body: current ? 'data: {"id":"evt_connected","type":"server.connected","data":{}}\n\n' : ": ok\n\n",
  })
 }
@@ -84,7 +84,6 @@ test("stages a submitted line comment in the prompt context", async ({ page }) =
 async function openReview(page: Page) {
  await page.setViewportSize({ width: 700, height: 900 })
  await mockOpenCodeServer(page, {
    protocol: "v2",
    directory,
    project: {
      id: "proj_review_line_comment_regression",
@@ -144,9 +143,9 @@ async function openReview(page: Page) {
  await page.goto(`/${base64Encode(directory)}/session/${sessionID}`)
  await expectSessionTitle(page, title)
-  const diffResponse = page.waitForResponse((response) => new URL(response.url()).pathname === "/api/vcs/diff")
+  const diffResponse = page.waitForResponse((response) => new URL(response.url()).pathname === "/vcs/diff")
  await page.getByRole("tab", { name: "Changes" }).click()
-  expect((await (await diffResponse).json()).data).toHaveLength(1)
+  expect(await (await diffResponse).json()).toHaveLength(1)
  const review = page.locator('[data-component="session-review"]')
  await expectAppVisible(review)
@@ -133,7 +133,7 @@ test("opens and searches project files inline", async ({ page }) => {
  await expect(panel.getByRole("tab", { name: "nested.ts" })).toHaveCount(1)
  await expect(panel.getByRole("tab", { name: "Open file" })).toHaveAttribute("data-selected", "")
  await expect(sidebarToggle).toBeDisabled()
-  await panel.locator("#session-side-panel-review-tab").click()
+  await panel.getByRole("tab", { name: /Review/ }).click()
  await expect(sidebarToggle).toBeEnabled()
  await panel.getByRole("tab", { name: "Open file" }).click()
  await page.keyboard.press("Control+w")
@@ -46,7 +46,7 @@ test("restores review mode and selected file per session", async ({ page }) => {
 async function selectMode(page: Page, current: string, next: string) {
  await page.getByRole("button", { name: current }).click()
-  await page.getByRole("option", { name: next }).dispatchEvent("click")
+  await page.getByRole("option", { name: next }).click()
 }
 async function selectFile(page: Page, file: string) {
@@ -65,7 +65,6 @@ async function switchSession(page: Page, title: string) {
 async function setup(page: Page) {
  await mockOpenCodeServer(page, {
    protocol: "v1",
    directory,
    project: {
      id: projectID,
@@ -20,12 +20,10 @@ const branchDiffs = [
 test("keeps the review tree and terminal sized when both panels are open", async ({ page }) => {
  test.setTimeout(120_000)
  const events: Array<{ directory: string; payload: Record<string, unknown> }> = []
  const sessionStatus = { [sessionID]: { type: "idle" as "busy" | "idle" } }
  let detailVersion = 1
  let detailFailures = 1
  await page.setViewportSize({ width: 1400, height: 900 })
  await mockOpenCodeServer(page, {
    protocol: "v1",
    directory,
    project: {
      id: projectID,
@@ -57,7 +55,7 @@ test("keeps the review tree and terminal sized when both panels are open", async
        time: { created: 1700000000000, updated: 1700000000000 },
      },
    ],
-    sessionStatus: () => sessionStatus,
+    sessionStatus: { [sessionID]: { type: "idle" } },
    pageMessages: () => ({ items: [] }),
    events: () => events.splice(0, 1),
    eventRetry: 16,
@@ -66,10 +64,7 @@ test("keeps the review tree and terminal sized when both panels are open", async
    route.fulfill({
      status: 200,
      contentType: "application/json",
-      body: JSON.stringify({
+      body: JSON.stringify({ branch: "review-pane-performance", default_branch: "dev" }),
        branch: "review-pane-performance",
        default_branch: "dev",
      }),
    }),
  )
  await page.route("**/vcs/diff**", (route) => {
@@ -91,51 +86,15 @@ test("keeps the review tree and terminal sized when both panels are open", async
      ),
    })
  })
-  await page.route("**/pty*", (route) =>
+  await page.route("**/pty", (route) =>
    route.fulfill({
      status: 200,
      contentType: "application/json",
-      body: JSON.stringify({
+      body: JSON.stringify({ id: "pty_review_terminal", title: "Terminal 1" }),
        location: { directory, project: { id: projectID, directory } },
        data: {
          id: "pty_review_terminal",
          title: "Terminal 1",
          command: "cmd.exe",
          args: [],
          cwd: directory,
          status: "running",
          pid: 1,
        },
      }),
    }),
  )
-  await page.route("**/pty/pty_review_terminal*", (route) =>
+  await page.route("**/pty/pty_review_terminal", (route) =>
-    route.fulfill({
+    route.fulfill({ status: 200, contentType: "application/json", body: "{}" }),
      status: 200,
      contentType: "application/json",
      body: JSON.stringify({
        location: { directory, project: { id: projectID, directory } },
        data: {
          id: "pty_review_terminal",
          title: "Terminal 1",
          command: "cmd.exe",
          args: [],
          cwd: directory,
          status: "running",
          pid: 1,
        },
      }),
    }),
  )
  await page.route("**/pty/pty_review_terminal/connect-token*", (route) =>
    route.fulfill({
      status: 200,
      contentType: "application/json",
      body: JSON.stringify({
        location: { directory, project: { id: projectID, directory } },
        data: { ticket: "e2e-ticket", expires_in: 60 },
      }),
    }),
  )
  await page.routeWebSocket("**/pty/pty_review_terminal/connect", () => undefined)
  await page.addInitScript(() => {
@@ -184,7 +143,6 @@ test("keeps the review tree and terminal sized when both panels are open", async
  const preview = page.locator('[data-slot="session-review-v2-diff-scroll"]')
  await expect(preview).toContainText("after-1")
  detailVersion = 2
  sessionStatus[sessionID] = { type: "busy" }
  events.push(statusEvent("busy"))
  await expect(page.getByRole("button", { name: "Stop" })).toBeVisible()
  const refreshedDiff = page.waitForRequest((request) => {
@@ -194,7 +152,6 @@ test("keeps the review tree and terminal sized when both panels are open", async
      url.searchParams.get("directory")?.replaceAll("\\", "/").endsWith("/src/branch/d00027") === true
    )
  })
  sessionStatus[sessionID] = { type: "idle" }
  events.push(statusEvent("idle"))
  await refreshedDiff
  await expect(preview).toContainText("after-2")
@@ -16,8 +16,8 @@ test("shows loaded sessions before the directory path request resolves", async (
  const pathBlocked = new Promise<void>((resolve) => {
    releasePath = resolve
  })
-  await page.route("**/api/path?*", async (route) => {
+  await page.route("**/path?*", async (route) => {
-    if (!new URL(route.request().url()).searchParams.has("location[directory]")) return route.fallback()
+    if (!new URL(route.request().url()).searchParams.has("directory")) return route.fallback()
    await pathBlocked
    return route.fallback()
  })
@@ -42,8 +42,7 @@ test("shows a pending question dock", async ({ page }) => {
  const rejectRequests: string[] = []
  page.on("request", (request) => {
    if (request.method() !== "POST") return
-    if (new URL(request.url()).pathname === `/api/session/${sessionID}/question/question-request/reject`)
+    if (new URL(request.url()).pathname === "/question/question-request/reject") rejectRequests.push(request.url())
      rejectRequests.push(request.url())
  })
  await question.locator('[data-component="icon-button"][data-icon="chevron-down"]').click()
@@ -65,9 +64,7 @@ test("shows a pending question dock", async ({ page }) => {
  await question.getByRole("radio", { name: /Minimal/ }).click()
  const reply = page.waitForRequest(
-    (request) =>
+    (request) => request.method() === "POST" && new URL(request.url()).pathname === "/question/question-request/reply",
      request.method() === "POST" &&
      new URL(request.url()).pathname === `/api/session/${sessionID}/question/question-request/reply`,
  )
  await question.getByRole("button", { name: "Submit" }).click()
  expect((await reply).postDataJSON()).toEqual({ answers: [["Minimal"]] })
@@ -100,8 +97,8 @@ test("shows a pending permission dock", async ({ page }) => {
  const reply = page.waitForRequest((request) => request.method() === "POST")
  await permission.getByRole("button", { name: "Allow once" }).click()
  const request = await reply
-  expect(new URL(request.url()).pathname).toBe(`/api/session/${sessionID}/permission/permission-request/reply`)
+  expect(new URL(request.url()).pathname).toBe(`/session/${sessionID}/permissions/permission-request`)
-  expect(request.postDataJSON()).toEqual({ reply: "once" })
+  expect(request.postDataJSON()).toEqual({ response: "once" })
 })
 test("restores the draft caret before typing after a request dock closes", async ({ page }) => {
@@ -173,7 +170,6 @@ async function mockServer(
  },
 ) {
  await mockOpenCodeServer(page, {
    protocol: "v2",
    directory,
    project: {
      id: projectID,
@@ -24,7 +24,7 @@ test("renders a completed single-file patch", async ({ page }) => {
      assistantMessage([
        toolPart(
          id,
-          "apply_patch",
+          "patch",
          "completed",
          { files: ["src/a.ts"] },
          {
@@ -35,7 +35,7 @@ test("preserves nested patch file state through outer collapse and reopen", asyn
      assistantMessage([
        toolPart(
          patchID,
-          "apply_patch",
+          "patch",
          "completed",
          { files: files.map((file) => file.filePath) },
          { metadata: { files } },
@@ -35,7 +35,6 @@ test.describe("session timeline projection", () => {
      editPart("prt_edit"),
      toolPart("prt_write", "write", "completed", { filePath: "src/new.ts", content: "export const stable = true\n" }),
      patchPart("prt_patch"),
      toolPart("prt_todo", "todowrite", "completed", { todos: [{ content: "Hidden", status: "pending" }] }),
      toolPart(
        "prt_question",
        "question",
@@ -65,7 +64,6 @@ test.describe("session timeline projection", () => {
    ]) {
      await expect(page.locator(`[data-timeline-part-id="${id}"]`).first(), id).toBeVisible()
    }
    await expect(page.locator('[data-timeline-part-id="prt_todo"]')).toHaveCount(0)
  })
  test("projects gaps, dividers, assistant parts, and errors together", async ({ page }) => {
@@ -249,7 +247,7 @@ function editPart(id: string) {
 function patchPart(id: string) {
  return toolPart(
    id,
-    "apply_patch",
+    "patch",
    "completed",
    { files: ["src/a.ts", "src/b.ts"] },
    {
@@ -8,7 +8,7 @@ import {
 } from "../performance/timeline-stability/fixture"
 test("renders every tool error outcome without leaking hidden tools", async ({ page }) => {
-  const ordinary = ["bash", "edit", "write", "apply_patch", "webfetch", "websearch", "task", "skill", "mcp_probe"]
+  const ordinary = ["bash", "edit", "write", "patch", "webfetch", "websearch", "task", "skill", "mcp_probe"]
  const parts = ordinary.map((tool, index) =>
    toolPart(`prt_error_${index}`, tool, "error", errorInput(tool), { error: `${tool} failed visibly` }),
  )
@@ -17,13 +17,11 @@ test("renders every tool error outcome without leaking hidden tools", async ({ p
      error: "The user dismissed this question",
    }),
    toolPart("prt_question_error", "question", "error", questionInput(), { error: "Question transport failed" }),
    toolPart("prt_todo_error", "todowrite", "error", { todos: [] }, { error: "Hidden todo failure" }),
  )
  await setupTimeline(page, { messages: [userMessage(), assistantMessage(parts)] })
  await expect(page.locator('[data-kind="tool-error-card"]')).toHaveCount(ordinary.length + 1)
  await expect(page.getByText(/dismissed/i)).toBeVisible()
  await expect(page.locator('[data-timeline-part-id="prt_todo_error"]')).toHaveCount(0)
  for (let index = 0; index < ordinary.length; index++) {
    await expect(page.locator(`[data-timeline-part-id="prt_error_${index}"]`)).toBeVisible()
  }
@@ -90,7 +88,7 @@ function questionInput() {
 function errorInput(tool: string) {
  if (tool === "bash") return { command: "exit 1" }
  if (["edit", "write"].includes(tool)) return { filePath: "src/error.ts", content: "" }
-  if (tool === "apply_patch") return { files: ["src/error.ts"] }
+  if (tool === "patch") return { files: ["src/error.ts"] }
  if (tool === "webfetch") return { url: "https://example.com" }
  if (tool === "websearch") return { query: "failure" }
  if (tool === "task") return { description: "Fail task", subagent_type: "explore" }
@@ -89,8 +89,8 @@ test("reconnects after a stream error", async ({ page }) => {
  expect((await timeline.transport.connections())[0]?.endedBy).toBe("error")
 })
-test("does not request replay when reconnecting the volatile V2 event stream", async ({ page }) => {
+test("records event IDs and reconnect Last-Event-ID headers", async ({ page }) => {
-  const timeline = await setupTimeline(page, { eventRetry: 10, protocol: "v2" })
+  const timeline = await setupTimeline(page, { eventRetry: 10 })
  const first = await timeline.transport.send(partUpdated(textPart("prt_transport_id", "event with id")), {
    id: "timeline-event-7",
  })
@@ -100,7 +100,7 @@ test("does not request replay when reconnecting the volatile V2 event stream", a
  const connection = await timeline.transport.waitForConnection({ after: first.connectionID })
  expect(first.eventID).toBe("timeline-event-7")
-  expect(connection.headers["last-event-id"]).toBeUndefined()
+  expect(connection.headers["last-event-id"]).toBe("timeline-event-7")
 })
 test("passes through non-event fetches", async ({ page }) => {
@@ -1,190 +0,0 @@
 import { base64Encode } from "@opencode-ai/core/util/encode"
 import { expect, test, type Page } from "@playwright/test"
 import { mockOpenCodeServer } from "../utils/mock-server"
 import { expectSessionTitle } from "../utils/waits"
 const directory = "C:/OpenCode/TodoDockNavigation"
 const projectID = "proj_todo_dock_navigation"
 const sourceID = "ses_todo_dock_source"
 const otherID = "ses_todo_dock_other"
 const sourceTitle = "Todo dock animation"
 const otherTitle = "Separate session"
 const activeTodos = [
  { id: "todo-1", content: "Receive todos in the active session", status: "completed", priority: "high" },
  { id: "todo-2", content: "Keep the dock visible across tabs", status: "completed", priority: "high" },
  { id: "todo-3", content: "Close after the final todo", status: "in_progress", priority: "high" },
 ]
 type EventPayload = {
  directory: string
  payload: Record<string, unknown>
 }
 test.use({ viewport: { width: 1440, height: 900 }, reducedMotion: "no-preference" })
 test("animates todo lifecycle without replaying it across session tabs", async ({ page }) => {
  test.setTimeout(90_000)
  const events: EventPayload[] = []
  const todos: Record<string, typeof activeTodos> = { [sourceID]: [], [otherID]: [] }
  const sessionStatus: Record<string, { type: "busy" | "idle" }> = {}
  await mockOpenCodeServer(page, {
    directory,
    project: {
      id: projectID,
      worktree: directory,
      vcs: "git",
      name: "todo-dock-navigation",
      time: { created: 1700000000000, updated: 1700000000000 },
      sandboxes: [],
    },
    provider: {
      all: [
        {
          id: "opencode",
          name: "OpenCode",
          models: {
            "claude-opus-4-6": {
              id: "claude-opus-4-6",
              name: "Claude Opus 4.6",
              limit: { context: 200_000 },
            },
          },
        },
      ],
      connected: ["opencode"],
      default: { providerID: "opencode", modelID: "claude-opus-4-6" },
    },
    sessions: [session(sourceID, sourceTitle, 1700000000000), session(otherID, otherTitle, 1700000001000)],
    sessionStatus: { [sourceID]: { type: "busy" } },
    pageMessages: () => ({ items: [] }),
    events: () => events.splice(0, 1),
    eventRetry: 16,
    sessionStatus: () => sessionStatus,
    todos: (sessionID) => todos[sessionID] ?? [],
  })
  await configurePage(page)
  await page.goto(sessionHref(sourceID))
  await expectSessionTitle(page, sourceTitle)
  const dock = page.locator('[data-component="session-todo-dock"]')
  await expect(dock).toHaveCount(0)
  sessionStatus[sourceID] = { type: "busy" }
  events.push(statusEvent(sourceID, "busy"))
  await expect(page.getByRole("button", { name: "Stop" })).toBeVisible()
  await page.waitForTimeout(700)
  const opening = sampleDock(page, 1_000)
  todos[sourceID] = activeTodos
  events.push(todoEvent(sourceID, activeTodos))
  await expect(dock).toBeVisible()
  await expect(dock.locator('[data-state="in_progress"]')).toHaveCount(1)
  expect((await opening).some((sample) => sample.opacity > 0.05 && sample.opacity < 0.95)).toBe(true)
  await switchSession(page, otherID, otherTitle)
  await expect(dock).toHaveCount(0)
  const returningOpen = sampleDock(page, 700)
  await switchSession(page, sourceID, sourceTitle)
  const openSamples = (await returningOpen).filter((sample) => sample.present)
  expect(openSamples.length).toBeGreaterThan(0)
  expect(openSamples[0]!.opacity).toBeGreaterThan(0.98)
  expect(openSamples[0]!.height).toBeGreaterThan(70)
  await expect(dock.locator('[data-state="in_progress"]')).toHaveCount(1)
  const completedTodos = activeTodos.map((todo) => ({ ...todo, status: "completed" }))
  const closing = sampleDock(page, 1_000)
  todos[sourceID] = completedTodos
  events.push(todoEvent(sourceID, completedTodos))
  await expect(dock).toHaveCount(0)
  expect((await closing).some((sample) => sample.opacity > 0.05 && sample.opacity < 0.95)).toBe(true)
  todos[sourceID] = []
  events.push(todoEvent(sourceID, []))
  await switchSession(page, otherID, otherTitle)
  const returningEmpty = sampleDock(page, 700)
  await switchSession(page, sourceID, sourceTitle)
  await expect(dock).toHaveCount(0)
  expect((await returningEmpty).every((sample) => !sample.present)).toBe(true)
 })
 function session(id: string, title: string, created: number) {
  return {
    id,
    slug: id,
    projectID,
    directory,
    title,
    version: "dev",
    time: { created, updated: created },
  }
 }
 function statusEvent(sessionID: string, type: "busy" | "idle"): EventPayload {
  return {
    directory,
    payload: { type: "session.status", properties: { sessionID, status: { type } } },
  }
 }
 function todoEvent(sessionID: string, next: typeof activeTodos): EventPayload {
  return {
    directory,
    payload: { type: "todo.updated", properties: { sessionID, todos: next } },
  }
 }
 async function configurePage(page: Page) {
  const server = `http://${process.env.PLAYWRIGHT_SERVER_HOST ?? "127.0.0.1"}:${process.env.PLAYWRIGHT_SERVER_PORT ?? "4096"}`
  await page.addInitScript(
    ({ directory, dirBase64, server, sessionIDs }) => {
      localStorage.setItem("settings.v3", JSON.stringify({ general: { newLayoutDesigns: true } }))
      localStorage.setItem(
        "opencode.global.dat:server",
        JSON.stringify({
          projects: { local: [{ worktree: directory, expanded: true }] },
          lastProject: { local: directory },
        }),
      )
      localStorage.setItem(
        "opencode.window.browser.dat:tabs",
        JSON.stringify(sessionIDs.map((sessionId) => ({ type: "session", server, dirBase64, sessionId }))),
      )
    },
    { directory, dirBase64: base64Encode(directory), server, sessionIDs: [sourceID, otherID] },
  )
 }
 function sessionHref(sessionID: string) {
  const server = `http://${process.env.PLAYWRIGHT_SERVER_HOST ?? "127.0.0.1"}:${process.env.PLAYWRIGHT_SERVER_PORT ?? "4096"}`
  return `/server/${base64Encode(server)}/session/${sessionID}`
 }
 async function switchSession(page: Page, sessionID: string, title: string) {
  const href = sessionHref(sessionID)
  const tab = page.locator(`[data-slot="titlebar-tabs"] a[href="${href}"]`).first()
  await expect(tab).toBeVisible()
  await tab.click()
  await expectSessionTitle(page, title)
 }
 function sampleDock(page: Page, duration: number) {
  return page.evaluate(async (duration) => {
    const samples: { present: boolean; height: number; opacity: number }[] = []
    const start = performance.now()
    while (performance.now() - start < duration) {
      const dock = document.querySelector<HTMLElement>('[data-component="session-todo-dock"]')
      const clip = dock?.parentElement?.parentElement
      const label = dock?.querySelector<HTMLElement>('[data-action="session-todo-toggle"] span[aria-label]')
      samples.push({
        present: !!dock,
        height: clip?.getBoundingClientRect().height ?? 0,
        opacity: label ? Number.parseFloat(getComputedStyle(label).opacity) : 0,
      })
      await new Promise(requestAnimationFrame)
    }
    return samples
  }, duration)
 }
--- a/Show More
+++ b/Show More