0be780052a
Bug fixes: - #52: bundle run-sleep.sh in Claude Code plugin + 4-level fallback - #58: add skillopt-sleep console script entry point in pyproject.toml - #62: filter headless claude -p replay sessions from harvest Plugin sync (Claude Code / Codex / Copilot / OpenClaw): - Document all 22 CLI flags, 7 actions, 4 backends across all SKILL.md files - Document config keys (preferences, gate_mode, dream_rollouts, etc.) - Document memory consolidation (evolve_memory / evolve_skill) - Add schedule/unschedule to all plugins - Copilot MCP: expand schema from 3 → 16 params + schedule tools - OpenClaw: add schedule/unschedule subcommands via shared scheduler Tests: - Cross-plugin parity test (prevents future feature drift) - MCP schema completeness test Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
SkillOpt-Sleep — GitHub Copilot integration
Give Copilot (CLI or VS Code) a nightly sleep cycle via a tiny MCP
server that exposes the skillopt_sleep engine as tools. MCP is GitHub's
supported way to extend Copilot, so this works across Copilot CLI, VS Code, and
other MCP clients with the same server.
What's here
| File | Purpose |
|---|---|
mcp_server.py |
stdlib-only MCP (stdio) server exposing sleep_* tools |
mcp-config.example.json |
drop-in MCP server config |
copilot-instructions.snippet.md |
paste into .github/copilot-instructions.md |
Install
Requires Python ≥ 3.10. No third-party packages — the server is pure stdlib.
-
Register the MCP server. Add the server to your Copilot MCP config (Copilot CLI:
~/.copilot/mcp-config.json; VS Code: your MCP settings). Usemcp-config.example.jsonas a template — setSKILLOPT_SLEEP_REPOto this repo's path:{ "mcpServers": { "skillopt-sleep": { "command": "python3", "args": ["/abs/path/SkillOpt-Sleep/plugins/copilot/mcp_server.py"], "env": { "SKILLOPT_SLEEP_REPO": "/abs/path/SkillOpt-Sleep" } } } } -
(Optional) Tell Copilot about it. Append
copilot-instructions.snippet.mdto your repo's.github/copilot-instructions.mdso Copilot reaches for the tools when the user asks to "run the sleep cycle".
Use
Ask Copilot things like "run the sleep cycle", "what did the last sleep
propose?", "adopt the staged sleep proposal". Copilot calls the MCP tools:
sleep_status, sleep_dry_run, sleep_run, sleep_adopt, sleep_harvest.
Each tool takes optional project, backend (mock/claude/codex/copilot), and
scope arguments. Default backend is mock (no API spend). The copilot
backend drives the GitHub Copilot CLI (copilot -p ... --output-format json)
and requires the copilot CLI to be installed and authenticated.
For speed, the copilot backend runs each call against an isolated
COPILOT_HOME with built-in MCP servers and custom instructions disabled, so
your user MCP servers (including this project's own) are not spawned per call
(~5x faster). Override with SKILLOPT_SLEEP_COPILOT_HOME=<dir>, pick a model
with SKILLOPT_SLEEP_COPILOT_MODEL, or set SKILLOPT_SLEEP_COPILOT_FULL_ENV=1
to use your real Copilot environment instead.
Verify the server directly (no Copilot needed)
printf '%s\n' \
'{"jsonrpc":"2.0","id":1,"method":"initialize","params":{}}' \
'{"jsonrpc":"2.0","id":2,"method":"tools/list"}' \
| SKILLOPT_SLEEP_REPO="$(pwd)" python3 plugins/copilot/mcp_server.py
You should see the server info and the five sleep_* tools.
Notes / status
- MCP is the stable, official Copilot extension surface, so this is the most portable of the three integrations (one server → CLI + IDE).
- The engine and all its controls (gate on/off, multi-rollout, budget, preferences, optimizer/target split) are identical across platforms — see the SkillOpt-Sleep guide section.