4e7add899d
Add skillopt/sleep — a deployment-time companion to SkillOpt that gives a
local Claude agent a nightly "sleep cycle":
harvest ~/.claude transcripts -> mine recurring tasks -> replay offline
-> consolidate (reflect -> bounded edit -> held-out GATE) -> stage -> adopt
Synthesizes SkillOpt (validation-gated bounded text optimization, reusing
skillopt.evaluation.gate verbatim), Claude Dreams (offline consolidation;
input never mutated; review-then-adopt), and the agent-sleep paper
(short-term experience -> long-term competence).
Engine (skillopt/sleep/, import-light, py>=3.10):
- harvest.py read-only parse of session JSONL + history.jsonl
- mine.py sessions -> TaskRecords (heuristic miner + LLM hook)
- backend.py MockBackend (deterministic, no API) + AnthropicBackend
- replay.py offline re-run -> (hard, soft) scores
- consolidate.py one SkillOpt epoch behind a held-out gate
- memory.py protected-region edits to SKILL.md / CLAUDE.md
- staging.py stage proposals; adopt with backup (Dreams safety contract)
- cycle.py + __main__.py orchestrator + CLI (run/dry-run/status/adopt/harvest)
Plugin (skillopt-sleep-plugin/): plugin.json, /sleep command, skillopt-sleep
skill, SessionEnd hook, bundled runner + cron generator.
Validation (deterministic, no API): persona experiment proves held-out lift
(researcher 0.33->1.0, programmer 0.32->1.0) AND that the gate rejects an
injected harmful edit. 13 stdlib-unittest tests pass, incl. full cycle +
adopt-with-backup and parsing of real on-disk transcripts.
Co-Authored-By: Claude Opus 4 <noreply@anthropic.com>
SkillOpt-Sleep (Claude Code plugin)
Give your local Claude agent a sleep cycle. Every night it reviews your past sessions offline, replays your recurring tasks on your own API budget, and consolidates what it learns into validated memory (
CLAUDE.md) and skills (SKILL.md). Your agent gets better the more you use it — no model-weight training.
SkillOpt-Sleep is the deployment-time companion to SkillOpt. SkillOpt trains a skill offline on a benchmark; SkillOpt-Sleep applies the same discipline to your own daily usage: bounded text edits, accepted only through a held-out validation gate, with rejected edits kept as negative feedback.
It synthesizes three ideas:
| Idea | Contribution |
|---|---|
| SkillOpt | skill/memory = trainable text; bounded add/delete/replace edits; held-out gate keeps only changes that help. |
| Claude Dreams | offline consolidation over past sessions; input never mutated; output reviewed then adopted. |
| Agent sleep | periodic offline replay turns short-term episodes into long-term skill. |
What it does (one "night")
harvest ~/.claude transcripts → mine recurring tasks → replay offline
→ consolidate (reflect → bounded edit → GATE) → stage proposal → (you) adopt
Nothing live is modified until you run /sleep adopt (the Dreams "review,
then adopt or discard" contract). Every adopt backs up the prior file first.
Quick start
# from inside any project you use with Claude Code:
/sleep dry-run # safe preview: what it would learn, no changes staged
/sleep run # full cycle: stages a reviewed proposal (still no live edits)
/sleep status # see history + the latest staged proposal
/sleep adopt # apply the staged proposal to CLAUDE.md / SKILL.md (with backup)
Or call the engine directly (Python ≥ 3.10):
python -m skillopt.sleep run --project "$(pwd)" --scope invoked --backend mock
python -m skillopt.sleep run --project "$(pwd)" --backend anthropic # real lift, uses your budget
Default backend is mock — deterministic, no API spend — so you can try the
plumbing for free. Switch to --backend anthropic for genuine improvement.
Does it actually improve? (deterministic proof)
python -m skillopt.sleep.experiments.run_experiment --persona researcher --assert-improves
python -m skillopt.sleep.experiments.run_experiment --persona programmer --assert-improves
Each prints the held-out score rising from baseline toward 1.0 as the gate
accepts the general rules your tasks need, and confirms the gate rejects an
injected harmful edit. Recorded output: docs/sleep/experiment_results.md.
Schedule it nightly
"${CLAUDE_PLUGIN_ROOT}/scripts/install-cron.sh" "$(pwd)" # prints a crontab line; installs nothing
Safety
- Read-only harvest of
~/.claude.mockreplay has no side effects. - Proposals are staged, never auto-applied (unless you opt in with
--auto-adopt). - Every adopt writes a backup under the staging dir's
backup/. - Per-night token/task budget caps; secrets redacted from prompts.
freshreplay (Phase 3) runs only in throwaway git worktrees.
Status
Phase 1 (engine + deterministic experiment + plugin surface) is complete.
Phase 3 adds the real-API miner/judge and fresh worktree replay. See
docs/superpowers/specs/2026-06-07-skillopt-sleep-claude-code-plugin-design.md.