rea/skills/reverse-engineer-anything/SKILL.md

name, description, metadata

name	description	metadata
reverse-engineer-anything	Reverse engineer native, managed, Electron/JavaScript, packaged, and browser applications with REA. Use shipped-artifact or requested runtime evidence to explain features, compare versions, decompile code, or guide a reconstruction. Skip REA for ordinary source-repository architecture analysis.	version tool_count catalog_digest 24 125 297aced29e7ce5e845c505d5f2e9e2dee42b7ed3e628f088f424fe8088c9e8dc

REA

Use REA when a claim depends on a shipped binary or package, decompilation, passive application runtime evidence, or comparison with behavior not established by available source. For ordinary analysis of a complete source repository, use normal repository tools and do not run REA readiness or provider commands.

Route the target first

Choose the first tool from the target the user supplied. Do not call open_binary unless the target is native or an analysis database.

• ASAR or extracted JavaScript/Electron tree: analyze_javascript_application.
• Archive, application package, ZIP/APK/IPA/MSIX/AppX, or DMG: open_binary with the supplied local path; use inspect_artifact when its graph and findings help answer the question.
• Managed PE/CLI assembly: inspect_managed_artifact.
• User-owned browser page already open: list_browser_targets.
• User-owned Electron runtime already open: list_electron_targets.
• Native executable, library, or analysis database: open_binary, then use focused analysis tools directly; call binary_overview when metadata or inventory context is useful.

If the app is missing, ask which app to inspect. Resolve a human-readable app name to one clear installed artifact when possible; ask only when matches are ambiguous. Never choose an example app on the user's behalf.

In a target-free session, use open_binary to bind any archive/package or native target whose analysis tool operates on the active target. Do not call a tool hidden from tools/list; inspect binary_session with detail: "capabilities" for the exact remediation when a desired capability is unavailable.

Work summary-first

Start with the default result and use its inline Evidence and graph context. Do not repeat an identical tool call. Make a focused follow-up only when the returned result leaves a specific question unanswered.

Every conclusion must distinguish observations, inferences, and unknowns. Cite Evidence IDs, preserve limitations and incomplete coverage, and never imply that static analysis observed execution. Runtime requests execute the declared target and lifecycle; do not broaden the target or action beyond those fields.

Within the user's requested investigation, call available analysis tools directly. REA does not require permission grants or per-call approval flags. Follow the declared request scope and the host's actual access requirements.

Plan broader investigations

For requests that span multiple features or subsystems, use a staged workflow:

1. Turn the request into a checklist of questions and the evidence each answer needs. Resolve target identity and constraints from the conversation and workspace before asking for information again.
2. Inspect the current REA session, artifact identity, saved analysis database, bookmarks, and prior evidence. Reuse matching state; do not open duplicate sessions or repeat identical analysis.
3. Start with the smallest useful overview or inventory. Follow each question from its entry point through relevant data and state changes to its result. Batch related operations around a specific hypothesis, then expand only when the returned evidence leaves a concrete gap.
4. Inspect relevant packaged resources and configuration alongside code when they affect the question. Use format-aware inventory and parsers; do not infer behavior from filenames, strings, or layout alone.
5. Corroborate a conclusion with the evidence type it requires. Use runtime observation only when static evidence cannot answer the question and the required host runtime and OS access are available. For JavaScript behavior, run probes against the actual app through the available browser, Electron, or process capture workflow.
6. Decompose work into independent questions. When parallel workers are available and the questions do not depend on one another, assign distinct scopes, point workers to existing evidence, and ask them to return sources, conclusions, and unresolved gaps. Otherwise, work sequentially.
7. Keep a concise finding ledger linking each conclusion to Evidence IDs, confidence/evidence type, search boundary, and remaining unknowns. Update the shared index or investigation report so later passes can reuse results.

Before finishing, revisit the original checklist. Mark each question as answered, partially answered, or unresolved based on its evidence; keep bounded negative searches bounded, and do not describe a broad investigation as complete while required questions remain open.

Read only the relevant guide

• Native binaries, managed assemblies, archives, and extraction: references/native-and-artifacts.md
• ASARs, extracted JavaScript, feature tracing, and version comparison: references/javascript-applications.md
• Passive browser/Electron observation and static/runtime reconciliation: references/runtime-observation.md
• Evidence paging, comparisons, residual unknowns, and verification: references/evidence-workflows.md

Readiness and setup

The readiness rule is conditional: when REA tools are available and their registration is not known to be stale, proceed directly; do not run doctor before every task. Run npx -y rea-agents@latest doctor when the MCP server or required provider is unavailable, registration is reported stale, or the user asks for an environment diagnosis. Propose npx -y rea-agents@latest setup only when doctor identifies an alignment or provider problem. Show the exact plan and obtain approval before setup writes configuration or installs Hopper. Restart the agent after MCP registration changes; direct CLI commands remain available immediately.

Finish the task

Explain findings in plain language and tie them to returned evidence. When the user asks to build something, use normal coding tools and separate observed behavior from design choices. Close an opened native session with close_binary when the investigation is complete.