fix(core): execute renamed tool definitions

packages/ai/AGENTS.md

@@ -10,7 +10,7 @@
 
 ## Conventions
 
-Per-type constructors live on the type, not as top-level re-exports. Use `Message.system(...)`, `Message.user(...)`, `Message.assistant(...)`, `Message.tool(...)`, `LanguageModel.make(...)`, `ToolDefinition.make(...)`, `ToolCallPart.make(...)`, `ToolResultPart.make(...)`, `ToolChoice.make(...)`, `ToolChoice.named(...)`, `SystemPart.make(...)`, and `GenerationOptions.make(...)` directly. The top-level `LLM` namespace is reserved for request-shaped call APIs: `LLM.request`, `LLM.generate`, `LLM.stream`, and `LLM.generateObject`. Use `LLMRequest.update(...)` when deriving canonical request data; do not add a duplicate `LLM.updateRequest(...)` path. Two ways to construct the same thing is one too many.
+Per-type constructors live on the type, not as top-level re-exports. Use `Message.system(...)`, `Message.user(...)`, `Message.assistant(...)`, `Message.tool(...)`, `LanguageModel.make(...)`, `ToolDefinition.make(...)`, `ToolCallPart.make(...)`, `ToolResultPart.make(...)`, `ToolChoice.make(...)`, `ToolChoice.named(...)`, `SystemPart.make(...)`, and `GenerationOptions.make(...)` directly. The top-level `LLM` namespace is reserved for request-shaped call APIs: `LLM.request`, `LLM.generate`, `LLM.stream`, `LLM.updateRequest`, and `LLM.generateObject`. Two ways to construct the same thing is one too many.
 
 - Keep provider-defined string enums forward-compatible. Expose known values for autocomplete while accepting future values with `Known | (string & {})`; use `Schema.String` at runtime unless rejecting unknown values is required for correctness.
 

packages/ai/README.md

@@ -3,9 +3,8 @@
 Schema-first AI primitives for opencode. Provider quirks live in adapters, not in calling code.
 
 ```ts
-import { Effect, Layer } from "effect"
+import { Effect } from "effect"
 import { LLM, LLMClient } from "@opencode-ai/ai"
-import { RequestExecutor } from "@opencode-ai/ai/route"
 import { OpenAI } from "@opencode-ai/ai/providers"
 
 const model = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).responses("gpt-4o-mini")
@@ -21,10 +20,6 @@ const program = Effect.gen(function* () {
   const response = yield* LLMClient.generate(request)
   console.log(response.text)
 })
-
-const llmLayer = LLMClient.layer.pipe(Layer.provide(RequestExecutor.fetchLayer))
-
-await Effect.runPromise(program.pipe(Effect.provide(llmLayer)))
 ```
 
 Run `LLMClient.stream(request)` instead of `generate` when you want incremental `LLMEvent`s. The event stream is provider-neutral — same shape across OpenAI Chat, OpenAI Responses, Anthropic Messages, Gemini, Bedrock Converse, and any OpenAI-compatible deployment.
@@ -205,32 +200,6 @@ The hosted result is represented as a provider-executed tool call and tool resul
 - **`Image.generate({...})`** — generate images through a provider-neutral image request and response model.
 - **`ImageClient`** — Effect service and layer for image execution, parallel to `LLMClient`.
 
-## Testing
-
-Use the deterministic test client from `@opencode-ai/ai/testing` to script provider-neutral responses and inspect
-the requests sent by code under test:
-
-```ts
-import { Effect } from "effect"
-import { TestLLM } from "@opencode-ai/ai/testing"
-
-const testLLM = TestLLM.layer({
-  fallback: TestLLM.text("Hello from the test model", "text-1"),
-})
-
-// TestLLM.clientLayer provides LLMClient.Service and consumes TestLLM.Service.
-const programWithTestClient = Effect.gen(function* () {
-  const result = yield* program
-  const test = yield* TestLLM.Service
-  console.log(test.requests)
-  return result
-}).pipe(Effect.provide(TestLLM.clientLayer), Effect.provide(testLLM))
-```
-
-`TestLLM.push(...)` scripts one-shot responses, `TestLLM.always(...)` changes the fallback, and
-`TestLLM.wait(...)` lets concurrent tests wait until a request has arrived. Every received canonical request is
-available on the yielded `TestLLM.Service`.
-
 ## Caching
 
 Prompt caching is **on by default**. Every `LLMRequest` resolves to `cache: "auto"` unless the caller opts out with `cache: "none"`. Each protocol translates `CacheHint`s to its wire format (`cache_control` on Anthropic, `cachePoint` on Bedrock; OpenAI and Gemini do implicit caching server-side and don't need inline markers — auto is a no-op there).

packages/ai/src/image-client.ts

@@ -15,11 +15,11 @@ export class Service extends Context.Service<Service, Interface>()("@opencode/Im
 
 export const generate = <Options extends ImageOptions>(
   request: ImageRequestFor<Options>,
-): Effect.Effect<ImageResponse, AIError, Service> =>
+): Effect.Effect<ImageResponse, AIError> =>
   Effect.gen(function* () {
     const client = yield* Service
     return yield* client.generate(request)
-  })
+  }) as Effect.Effect<ImageResponse, AIError>
 
 export const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(
   Service,

packages/ai/src/llm.ts

@@ -1,5 +1,5 @@
 import { Effect, JsonSchema, Schema } from "effect"
-import { LLMClient, Service } from "./route/client"
+import { LLMClient } from "./route/client"
 import {
   GenerationOptions,
   HttpOptions,
@@ -151,10 +151,10 @@ const runGenerateObject = Effect.fn("LLM.generateObject")(function* (
  */
 export function generateObject<const SelectedLanguageModel extends LanguageModel, S extends ToolSchema<any>>(
   options: GenerateObjectOptions<S, SelectedLanguageModel>,
-): Effect.Effect<GenerateObjectResponse<Schema.Schema.Type<S>>, AIError, Service>
+): Effect.Effect<GenerateObjectResponse<Schema.Schema.Type<S>>, AIError>
 export function generateObject<const SelectedLanguageModel extends LanguageModel>(
   options: GenerateObjectDynamicOptions<SelectedLanguageModel>,
-): Effect.Effect<GenerateObjectResponse<unknown>, AIError, Service>
+): Effect.Effect<GenerateObjectResponse<unknown>, AIError>
 export function generateObject(options: GenerateObjectOptions<ToolSchema<any>> | GenerateObjectDynamicOptions) {
   if ("schema" in options) {
     const { schema, ...rest } = options

packages/ai/src/route/client.ts

@@ -422,18 +422,18 @@ const generateWith = (stream: Interface["stream"]) =>
     )
   })
 
-export function stream(request: LLMRequest, options?: StreamOptions): Stream.Stream<LLMEvent, AIError, Service> {
+export function stream(request: LLMRequest, options?: StreamOptions): Stream.Stream<LLMEvent, AIError> {
   return Stream.unwrap(
     Effect.gen(function* () {
       return (yield* Service).stream(request, options)
     }),
-  )
+  ) as Stream.Stream<LLMEvent, AIError>
 }
 
-export function generate(request: LLMRequest, options?: StreamOptions): Effect.Effect<LLMResponse, AIError, Service> {
+export function generate(request: LLMRequest, options?: StreamOptions): Effect.Effect<LLMResponse, AIError> {
   return Effect.gen(function* () {
     return yield* (yield* Service).generate(request, options)
-  })
+  }) as Effect.Effect<LLMResponse, AIError>
 }
 
 export const streamRequest = (request: LLMRequest, options?: StreamOptions) =>

packages/ai/test/image.types.ts

@@ -1,7 +1,5 @@
-import { Effect } from "effect"
 import {
   Image,
-  ImageClient,
   ImageInput,
   ImageModel,
   type ImageModelOptions,
@@ -9,13 +7,8 @@ import {
   type ImageRequestFor,
   type ImageRoute,
 } from "../src"
-import type { Service } from "../src/image-client"
 import { Google, OpenAI, XAI, ZAI } from "../src/providers"
 
-type Requirements<T> = T extends Effect.Effect<infer _A, infer _E, infer R> ? R : never
-type Equal<A, B> = [A, B] extends [B, A] ? true : false
-type Assert<T extends true> = T
-
 type GoogleLikeOptions = {
   readonly aspectRatio?: "1:1" | "16:9"
   readonly imageSize?: "1K" | "2K"
@@ -153,9 +146,6 @@ const request = Image.request({
 })
 const typedRequest: ImageRequestFor<GoogleLikeOptions> = request
 void typedRequest
-const generated = ImageClient.generate(request)
-type GenerateRequirements = Assert<Equal<Requirements<typeof generated>, Service>>
-void (true satisfies GenerateRequirements)
 
 // @ts-expect-error Image requests no longer expose a common count option.
 Image.generate({ model: openai, prompt: "A lighthouse", count: 2 })

packages/ai/test/llm-option-types.types.ts

@@ -1,11 +1,5 @@
-import { Effect, Schema, Stream } from "effect"
-import {
-  LLM,
-  type LLMClientService,
-  type LanguageModel,
-  type LanguageModelProviderOptions,
-  type ProviderOptions,
-} from "../src"
+import { Schema } from "effect"
+import { LLM, type LanguageModel, type LanguageModelProviderOptions, type ProviderOptions } from "../src"
 import { OpenAIChat } from "../src/protocols"
 
 interface ExampleOptions {
@@ -21,19 +15,9 @@ const model = OpenAIChat.route
   .with({ endpoint: { baseURL: "https://example.com/v1" } })
   .model<ExampleProviderOptions>({ id: "example" })
 
-type Requirements<T> = T extends Effect.Effect<infer _A, infer _E, infer R> ? R : never
-type StreamRequirements<T> = T extends Stream.Stream<infer _A, infer _E, infer R> ? R : never
-type Equal<A, B> = [A, B] extends [B, A] ? true : false
-type Assert<T extends true> = T
-
 LLM.request({ model, prompt: "Hello", providerOptions: { example: { mode: "fast" } } })
 LLM.request({ model, prompt: "Hello", providerOptions: { future: { option: true } } })
 
-const generated = LLM.generate(LLM.request({ model, prompt: "Hello" }))
-type GenerateRequirements = Assert<Equal<Requirements<typeof generated>, LLMClientService>>
-const streamed = LLM.stream(LLM.request({ model, prompt: "Hello" }))
-type StreamClientRequirements = Assert<Equal<StreamRequirements<typeof streamed>, LLMClientService>>
-
 LLM.request({
   model,
   prompt: "Hello",
@@ -41,20 +25,12 @@ LLM.request({
   providerOptions: { example: { mode: "slow" } },
 })
 
-const generatedObject = LLM.generateObject({
+LLM.generateObject({
   model,
   prompt: "Hello",
   schema: Schema.Struct({ answer: Schema.String }),
   providerOptions: { example: { mode: "thorough" } },
 })
-type GenerateObjectRequirements = Assert<Equal<Requirements<typeof generatedObject>, LLMClientService>>
-
-const generatedDynamicObject = LLM.generateObject({
-  model,
-  prompt: "Hello",
-  jsonSchema: { type: "object" },
-})
-type GenerateDynamicObjectRequirements = Assert<Equal<Requirements<typeof generatedDynamicObject>, LLMClientService>>
 
 LLM.generateObject({
   model,
@@ -68,8 +44,4 @@ declare const generic: LanguageModel
 LLM.request({ model: generic, prompt: "Hello", providerOptions: { arbitrary: { option: true } } })
 
 const options: LanguageModelProviderOptions<typeof model> = { example: { mode: "fast" } }
-void (options satisfies LanguageModelProviderOptions<typeof model>)
-void (true satisfies GenerateRequirements)
-void (true satisfies StreamClientRequirements)
-void (true satisfies GenerateObjectRequirements)
-void (true satisfies GenerateDynamicObjectRequirements)
+void options

packages/core/src/session/model-request.ts

@@ -191,22 +191,31 @@ export const layer = Layer.effect(
       const messages = stepLimitReached ? [...history, Message.assistant(MAX_STEPS_PROMPT)] : history
       const toolDefinitions = tools.definitions
       const toolsByName = new Map(toolDefinitions.map((tool) => [tool.name, tool]))
+      // Object identity preserves registry provenance when a hook moves a definition to a new key.
+      const toolNamesByDefinition = new Map<object, string>()
       // Hooks may reshape available definitions but cannot advertise tools omitted by permissions or the Step limit.
+      const hookTools = Object.fromEntries(
+        toolDefinitions.map((tool) => {
+          const definition = { description: tool.description, input: { ...tool.inputSchema } }
+          toolNamesByDefinition.set(definition, tool.name)
+          return [tool.name, definition]
+        }),
+      )
       const contextEvent = yield* hooks.trigger("session", "context", {
         sessionID: session.id,
         agent: agent.id,
         model: resolved.ref,
         system,
         messages,
-        tools: Object.fromEntries(
-          toolDefinitions.map((tool) => [tool.name, { description: tool.description, input: { ...tool.inputSchema } }]),
-        ),
+        tools: hookTools,
       })
+      const executableTools = new Map<string, string>()
       const hookedTools = Object.entries(contextEvent.tools).flatMap(([name, tool]) => {
-        const registered = toolsByName.get(name)
-        return registered
-          ? [{ ...registered, description: tool.description, inputSchema: tool.input }]
-          : []
+        const registeredName = toolNamesByDefinition.get(tool)
+        const registered = registeredName ? toolsByName.get(registeredName) : undefined
+        if (!registered || !registeredName) return []
+        executableTools.set(name, registeredName)
+        return [{ ...registered, name, description: tool.description, inputSchema: tool.input }]
       })
       const request = LLM.request({
         model,
@@ -259,10 +268,14 @@ export const layer = Layer.effect(
       const executeTool: Prepared["executeTool"] = (executeInput) => {
         if (stepLimitReached)
           return new Tool.Error({ message: "Tools are disabled after the maximum agent steps" })
-        if (toolsByName.has(executeInput.call.name) && !Object.hasOwn(contextEvent.tools, executeInput.call.name))
+        const registeredName = executableTools.get(executeInput.call.name)
+        if (!registeredName && toolsByName.has(executeInput.call.name))
           return new Tool.Error({ message: `Tool is not available for this request: ${executeInput.call.name}` })
         return tools
-          .execute(executeInput)
+          .execute({
+            ...executeInput,
+            call: { ...executeInput.call, name: registeredName ?? executeInput.call.name },
+          })
           .pipe(Effect.catchCauseFilter(declineDefect, (decline) => Effect.fail(decline)))
       }
       return {

packages/core/test/session-runner.test.ts

@@ -887,6 +887,42 @@ describe("SessionRunnerLLM", () => {
     }),
   )
 
+  it.effect("advertises and executes a tool renamed by a session context hook", () =>
+    Effect.gen(function* () {
+      const session = yield* setup
+      const hooks = yield* PluginHooks.Service
+      yield* hooks.register("session", "context", (event) =>
+        Effect.sync(() => {
+          const tool = event.tools.echo
+          if (!tool) return
+          event.tools.renamed_echo = tool
+          delete event.tools.echo
+        }),
+      )
+      yield* admit(session, "Use the renamed tool")
+      yield* TestLLM.push(TestLLM.tool("call-renamed", "renamed_echo", { text: "renamed" }), [])
+
+      yield* session.resume(sessionID)
+
+      expect(requests[0]?.tools.map((tool) => tool.name)).toContain("renamed_echo")
+      expect(requests[0]?.tools.map((tool) => tool.name)).not.toContain("echo")
+      expect(executions).toEqual(["renamed"])
+      expect(yield* session.context(sessionID)).toMatchObject([
+        { type: "user", text: "Use the renamed tool" },
+        {
+          type: "assistant",
+          content: [
+            {
+              type: "tool",
+              id: "call-renamed",
+              state: { status: "completed", content: [{ type: "text", text: "renamed" }] },
+            },
+          ],
+        },
+      ])
+    }),
+  )
+
   it.effect("advertises and executes a location registered tool", () =>
     Effect.gen(function* () {
       const session = yield* setup

packages/core/test/tool-shell.test.ts

@@ -301,7 +301,6 @@ describe("ShellTool", () => {
       },
       (tmp) => Effect.promise(() => tmp[Symbol.asyncDispose]().then(() => undefined)),
     ),
-    { timeout: 15_000 },
   )
 
   it.live("rejects a workdir that stops being a directory during approval", () =>
@@ -473,7 +472,6 @@ describe("ShellTool", () => {
       },
       (tmp) => Effect.promise(() => tmp[Symbol.asyncDispose]().then(() => undefined)),
     ),
-    { timeout: 15_000 },
   )
 
   it.live(
@@ -540,7 +538,7 @@ describe("ShellTool", () => {
       (tmp) => {
           reset()
           return withSession(tmp.path, (registry) =>
-            executeTool(registry, call({ command: timeoutOutputCommand, timeout: isWindows ? 3_000 : 50 })),
+            executeTool(registry, call({ command: timeoutOutputCommand, timeout: isWindows ? 500 : 50 })),
           ).pipe(
             Effect.andThen((settled) =>
               Effect.sync(() => {
@@ -559,7 +557,6 @@ describe("ShellTool", () => {
       },
       (tmp) => Effect.promise(() => tmp[Symbol.asyncDispose]().then(() => undefined)),
     ),
-    { timeout: 15_000 },
   )
 
   it.live("returns the shell id for a background command", () =>