Yif-Yang
57 lines
2.8 KiB
Markdown
57 lines
2.8 KiB
Markdown
<!--
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Copy this block into your repo's .github/copilot-instructions.md so Copilot
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knows the SkillOpt-Sleep tools exist. (Copilot reads copilot-instructions.md
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automatically as ambient guidance.)
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-->
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## SkillOpt-Sleep (offline self-evolution)
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This project has SkillOpt-Sleep available via an MCP server (`skillopt-sleep`).
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It gives the agent a nightly "sleep cycle": it reviews past sessions, replays
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recurring tasks through a selected backend, and stages validation-gated changes
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to project `CLAUDE.md` and a configured `SKILL.md`.
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When the user asks to "run the sleep cycle", "review my past sessions", "learn
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my preferences", or "make the agent improve from past usage", use the MCP tools:
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- `sleep_status` — what's happened + the latest staged proposal
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- `sleep_dry_run` — no-staging preview; a real backend still makes provider calls
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- `sleep_run` — full cycle, stages a validation-gated proposal by default;
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explicit `auto_adopt` may update live files
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- `sleep_adopt` — apply the staged proposal (backs up an existing live file first)
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- `sleep_harvest` — list mined recurring tasks
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- `sleep_schedule` — install a nightly cron entry (set `hour`/`minute`)
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- `sleep_unschedule` — remove the nightly cron entry
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### Key parameters (pass as MCP tool arguments)
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- `backend` — `mock` (default, no provider calls), `claude`, `codex`, or `copilot`
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- `source` — `claude`, `codex`, or `auto` (where to read transcripts)
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- `target_skill_path` — explicit SKILL.md to evolve; use this for a skill that
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the current agent actually loads
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- `tasks_file` — reviewed TaskRecord JSON (skip harvest); real backends require
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its metadata to contain `"reviewed": true`
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- `max_tasks` / `max_sessions` — cap workload
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- `auto_adopt` — auto-adopt if the gate passes
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- `json` — machine-readable output for programmatic use
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### Advanced config (`~/.skillopt-sleep/config.json`)
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- `preferences` — free-text house rules for the optimizer
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- `gate_mode` — `on` (default) or `off`; `dream_rollouts` — >1 for more signal
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- `evolve_memory` / `evolve_skill` — toggle which docs consolidate
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Always show the user the held-out baseline → candidate score and the proposed
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edits before suggesting `sleep_adopt`. Never hand-edit the user's memory/skill
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files; use `sleep_adopt` (or an explicitly requested `auto_adopt`) so the engine
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applies its staging manifest and backup behavior.
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Harvesting is local and read-only, and `backend: "mock"` makes no provider
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calls. A real backend sends truncated transcript excerpts and derived tasks to
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the selected provider; outbound prompts are not guaranteed to be secret-free.
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Review sensitive data and provider policy before selecting a real backend.
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`sleep_schedule` persists only the project, backend, time, and optional
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auto-adopt setting. Put a non-default transcript source or target skill in
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`~/.skillopt-sleep/config.json` before scheduling it.
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