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Yifan Yang f9db99853b feat(plugins): ship SkillOpt-Sleep for Claude Code, Codex, and Copilot

Restructure into plugins/{claude-code,codex,copilot}/ — one engine, three thin
shells, all calling the shared plugins/run-sleep.sh -> python -m skillopt_sleep.

  - claude-code/: existing plugin moved here; runner delegates to the shared
    launcher (fixes repo-root resolution after the move).
  - codex/: ~/.codex/prompts/sleep.md custom prompt + ~/.agents/skills SKILL.md +
    install.sh + AGENTS.md hint — Codex's documented, stable extension surfaces.
  - copilot/: a stdlib-only MCP server (mcp_server.py) exposing sleep_* tools,
    plus mcp-config.example.json and a copilot-instructions snippet. Verified end
    to end (initialize -> tools/list -> tools/call returns real engine output).
  - plugins/README.md overview table; main README News + a dedicated SkillOpt-Sleep
    section; pyproject lists skillopt_sleep as a first-class package.

Decoupling emphasized throughout: open-source tool (skillopt_sleep/) with zero
dependency on the research package. 29 tests pass; all three shells resolve.

Co-Authored-By: Claude Opus 4 <noreply@anthropic.com>

2026-06-08 14:31:52 +00:00

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name, description

name	description
skillopt-sleep	Nightly offline self-evolution for a Codex agent. Reviews past sessions, replays recurring tasks, and consolidates validated memory + skills behind a held-out gate. Use when the user wants Codex to learn from past usage, run a "sleep"/"dream" cycle, or schedule offline self-optimization.

SkillOpt-Sleep (Codex skill)

This skill drives the skillopt_sleep engine — an offline "sleep cycle" that makes a Codex agent better at the user's recurring work without retraining.

When to use

Trigger when the user wants to: review past sessions, learn their preferences, consolidate feedback into long-term memory/skills, run a nightly/offline self-improvement cycle, or adopt a staged proposal.

How to run it

Invoke the bundled runner via shell (Codex exec has shell access). The runner finds the engine and a Python ≥ 3.10 automatically:

# point at the repo if it isn't auto-detected from CWD:
export SKILLOPT_SLEEP_REPO=/path/to/SkillOpt-Sleep
bash "$SKILLOPT_SLEEP_REPO/plugins/run-sleep.sh" <action> --project "$(pwd)"

<action> ∈ status | dry-run | run | adopt | harvest. Use --backend codex for real improvement on the user's own Codex budget (default mock = no spend).

Steps

Run the requested action; capture stdout.
For run/dry-run: read the staged report.md it prints and show the user the held-out baseline → candidate score and the exact proposed edits.
run only stages a proposal under <project>/.skillopt-sleep/staging/; nothing live changes until adopt. Offer /sleep adopt.
Never hand-edit the user's AGENTS.md / skills yourself — only adopt does, and it backs up first.

Validate

python -m skillopt_sleep.experiments.run_gbrain --backend codex \
  --seeds brief-writer --data-root /path/to/gbrain-evals/eval/data/skillopt-v1 \
  --nights 2 --limit-replay 3 --limit-holdout 3

A deficient skill goes 0.00 → 1.00 on a held-out set; the optimizer's edits are gated on real-task performance.

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