VS Code Copilot Extension Integration Plan

1. Groundwork

Audit existing claude-mem hook scripts (context-hook, user-message-hook, new-hook, save-hook, summary-hook, cleanup-hook) and their worker-service payloads.
Document REST endpoints, request bodies, and SessionStore schema fields used today so the extension mirrors them exactly.
Confirm worker service availability workflow (ensureWorkerRunning, port resolution) and decide how extension error reporting will surface issues to Copilot chat users.

Clone the VS Code chat-sample starter, convert to a TypeScript-only extension, and align lint/tsconfig with repo standards.
Add build pipeline (esbuild or webpack) plus npm scripts that match the existing scripts/build-hooks.js release flow.
Wire extension activation events for chat participation and ensure packaging metadata (publisher, categories) is in place.

Extract reusable worker-service client utilities from plugin/scripts/*.js (port discovery, session init, observation uploads).
Publish TypeScript definitions by re-exporting from src/services/worker-types.ts to keep contracts synchronized.
Centralize HTTP calls (timeouts, retries, logging) so every tool implementation uses the same helper layer.

Add contributes.languageModelTools entries in package.json for lifecycle parity:
- mem_session_init, mem_user_prompt_log, mem_observation_record, mem_summary_finalize, mem_session_cleanup.
Provide detailed JSON schemas mirroring hook input structures (session IDs, cwd, prompt text, tool payload metadata).
Supply descriptive modelDescription, userDescription, icons, tags, and enable canBeReferencedInPrompt where appropriate.

Register each tool via vscode.lm.registerTool inside activate.
Implement prepareInvocation to show user confirmations (especially for cleanup/stop actions) and tailor messages to match existing CLI prompts.
In invoke, call the shared worker client, translate successes into LanguageModelToolResult text parts, and craft error messages that guide the LLM toward recovery (retry, alternate parameters).
Ensure telemetry/logging records tool usage for debugging without leaking sensitive data.

Implement a chat participant based on the sample that maps Copilot threads to claude-mem session IDs stored in turn metadata.
On conversation start, auto-run mem_session_init; before each user prompt, dispatch mem_user_prompt_log; when Copilot signals stop, run mem_summary_finalize (with fallbacks if the worker is unavailable).
Capture tool events emitted by Copilot (file edits, terminal runs) and forward them through mem_observation_record with matching payload structure.
Handle conversation disposal or model changes by calling mem_session_cleanup to mirror SessionEnd hooks.

Read .claude-mem/settings.json overrides (worker port, observation depth) and surface VS Code settings for Copilot-specific toggles (auto-sync enabled, max observations per prompt).
Add status bar indicator/commands for worker health, quick restart instructions, and opening the viewer UI (http://localhost:37777).
Provide inline notifications when the worker is unreachable, including guidance to restart via PM2.

Draft manual validation checklist: initial session, prompt logging, observation capture, summary completion, worker-down handling.
Add integration tests using @vscode/test-electron to simulate chat turns and assert database side effects in a temporary claude-mem data directory.
Build mocks for worker endpoints to enable unit tests of tool invocation logic without hitting the real service.

Document installation and usage in README.md, including architecture diagrams showing Copilot → tool → worker flow.
Update CHANGELOG and marketing copy to announce Copilot support and list prerequisites (worker running, settings file placement).
Prepare Marketplace assets (icon, gallery text) and extend existing publish scripts to package and ship the new extension.