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microsoft-SkillOpt/plugins/copilot/copilot-instructions.snippet.md
carpedkm 0be780052a feat: sync all 4 runtime plugins with full engine surface + fix #52 #58 #62 
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>
2026-06-20 11:31:09 +00:00

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SkillOpt-Sleep (offline self-evolution)

This project has SkillOpt-Sleep available via an MCP server (skillopt-sleep). It gives the agent a nightly "sleep cycle": it reviews past sessions, replays recurring tasks offline, and consolidates validated memory + skills behind a held-out gate.

When the user asks to "run the sleep cycle", "review my past sessions", "learn my preferences", or "make the agent improve from past usage", use the MCP tools:

  • sleep_status — what's happened + the latest staged proposal
  • sleep_dry_run — safe preview, stages nothing
  • sleep_run — full cycle, stages a reviewed proposal (nothing live changes)
  • sleep_adopt — apply the staged proposal (backs up first)
  • sleep_harvest — list mined recurring tasks
  • sleep_schedule — install a nightly cron entry (set hour/minute)
  • sleep_unschedule — remove the nightly cron entry

Key parameters (pass as MCP tool arguments)

  • backend — mock (default, free), claude, codex, or copilot
  • source — claude, codex, or auto (where to read transcripts)
  • target_skill_path — explicit SKILL.md to evolve
  • tasks_file — pre-built TaskRecord JSON (skip harvest)
  • max_tasks / max_sessions — cap workload
  • auto_adopt — auto-adopt if the gate passes
  • json — machine-readable output for programmatic use

Advanced config (~/.skillopt-sleep/config.json)

  • preferences — free-text house rules for the optimizer
  • gate_mode — on (default) or off; dream_rollouts — >1 for more signal
  • evolve_memory / evolve_skill — toggle which docs consolidate

Always show the user the held-out baseline → candidate score and the proposed edits before suggesting sleep_adopt. Never hand-edit the user's memory/skill files; only sleep_adopt does that, with a backup.

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