feat(sleep): nightly offline self-evolution engine + Claude Code plugin

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>
This commit is contained in:
Yifan Yang
2026-06-08 14:31:51 +00:00
parent 0ac2b35daa
commit 4e7add899d
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{
"name": "skillopt-sleep",
"description": "Give your local Claude agent a nightly 'sleep cycle': it reviews your past sessions offline, replays recurring tasks on your own API budget, and consolidates what it learns into validated memory (CLAUDE.md) and skills (SKILL.md).越用越好用 — gets better the more you use it. Synthesizes SkillOpt (validation-gated skill optimization), Claude Dreams (offline memory consolidation), and agent sleep/consolidation.",
"version": "0.1.0",
"author": {
"name": "Yifan Yang",
"email": "yifanyang@microsoft.com"
},
"homepage": "https://github.com/microsoft/SkillOpt",
"repository": "https://github.com/microsoft/SkillOpt",
"license": "MIT",
"keywords": [
"skillopt",
"self-improvement",
"memory-consolidation",
"dreams",
"sleep",
"skills",
"continual-learning",
"offline-optimization"
]
}
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# 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](https://github.com/microsoft/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
```bash
# 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):
```bash
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)
```bash
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`](../docs/sleep/experiment_results.md).
## Schedule it nightly
```bash
"${CLAUDE_PLUGIN_ROOT}/scripts/install-cron.sh" "$(pwd)" # prints a crontab line; installs nothing
```
## Safety
- **Read-only** harvest of `~/.claude`. `mock` replay 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.
- `fresh` replay (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`](../docs/superpowers/specs/2026-06-07-skillopt-sleep-claude-code-plugin-design.md).
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---
description: Run or manage the SkillOpt-Sleep self-evolution cycle (review past sessions, replay tasks offline, consolidate validated memory + skills)
argument-hint: "[run | dry-run | status | adopt | harvest] (default: status)"
allowed-tools: Bash, Read
---
# /sleep — SkillOpt-Sleep nightly self-evolution
You are driving **SkillOpt-Sleep**: a tool that lets this user's Claude agent
improve offline by reviewing past sessions, replaying recurring tasks, and
consolidating what it learns into **validated** memory (`CLAUDE.md`) and skills
(`SKILL.md`). It is gated like SkillOpt: a change is kept only if it improves a
held-out replay score, and nothing live is modified until the user adopts it.
## Requested action: $ARGUMENTS
(If `$ARGUMENTS` is empty, treat it as `status`.)
## How to run it
The engine is the `skillopt.sleep` Python package in this repo. Use the
**plugin's bundled runner** so the right interpreter and repo are on the path:
```bash
"${CLAUDE_PLUGIN_ROOT}/scripts/sleep.sh" <action> --project "$(pwd)" --scope invoked
```
`<action>` is one of:
| action | what it does |
|-----------|--------------|
| `status` | show how many nights have run + the latest staged proposal (READ-ONLY) |
| `dry-run` | harvest → mine → replay → report, but **stage nothing** (safe preview) |
| `run` | full cycle: also **stage** a reviewed proposal (still does NOT touch live files) |
| `adopt` | apply the latest staged proposal to live `CLAUDE.md` / `SKILL.md` (backs up first) |
| `harvest` | debug: print the recurring tasks mined from recent sessions |
Default backend is `mock` (deterministic, no API spend). To use real Anthropic
budget for genuine improvement, add `--backend anthropic`.
## Steps to follow
1. **Run the requested action** via the bundled runner above. Capture stdout.
2. **For `run` / `dry-run`:** after it completes, `Read` the generated
`report.md` in the staging dir it prints, and show the user:
- held-out score: baseline → candidate (the proof it helped)
- the gate decision (accept/reject) and the exact edits it proposes
- where the proposal is staged
3. **For `run` that produced an accepted proposal:** tell the user the diff is
staged and that **nothing live changed yet**. Offer to run `/sleep adopt`.
4. **For `adopt`:** confirm which live files were updated and that backups were
written under the staging dir's `backup/`.
5. **Never** edit `CLAUDE.md` or `SKILL.md` yourself — only the `adopt` action
does that, with a backup. Respect the review gate.
## Safety reminders
- Harvest is **read-only** over `~/.claude`. Replay in `mock` mode runs no
shell side effects.
- The cycle stages proposals; the user is in control of adoption.
- If the user asks to schedule this nightly, point them at
`${CLAUDE_PLUGIN_ROOT}/scripts/install-cron.sh` (prints a crontab line; does
not install anything without confirmation).
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{
"hooks": {
"SessionEnd": [
{
"matcher": "*",
"hooks": [
{
"type": "command",
"command": "\"${CLAUDE_PLUGIN_ROOT}/hooks/on-session-end.sh\"",
"async": true
}
]
}
]
}
}
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#!/usr/bin/env bash
# SkillOpt-Sleep SessionEnd hook (async, best-effort, NON-BLOCKING).
#
# This does NOT run the optimizer. It only appends a tiny marker so the next
# nightly cycle knows there is fresh activity to harvest, and (optionally)
# nudges the user once that a sleep cycle is available. It must never fail the
# session or spend API budget.
set -uo pipefail
PLUGIN_ROOT="${CLAUDE_PLUGIN_ROOT:-$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)}"
STATE_DIR="${HOME}/.skillopt-sleep"
mkdir -p "$STATE_DIR" 2>/dev/null || exit 0
# Record that a session just ended (cheap; used for "is there new data?").
printf '%s\t%s\n' "$(date -u +%Y-%m-%dT%H:%M:%SZ)" "${PWD}" \
>> "$STATE_DIR/session-end.log" 2>/dev/null || true
exit 0
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#!/usr/bin/env bash
# Print (does NOT install) a crontab line that runs SkillOpt-Sleep nightly.
# The user copies the line into `crontab -e` if they want it.
set -euo pipefail
PLUGIN_ROOT="${CLAUDE_PLUGIN_ROOT:-$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)}"
RUNNER="$PLUGIN_ROOT/scripts/sleep.sh"
PROJECT="${1:-$(pwd)}"
BACKEND="${2:-mock}"
# 3:17am local — deliberately off the :00 mark so many users don't all hit the
# API at once (and we leave room for jitter).
MIN=17
HOUR=3
cat <<EOF
# ── SkillOpt-Sleep nightly cycle ────────────────────────────────────────────
# Review past sessions, replay tasks, stage validated memory/skill updates.
# Runs at ${HOUR}:$(printf '%02d' $MIN) local every day. Output goes to the project's
# .skillopt-sleep/ dir; nothing live is changed until you run '/sleep adopt'
# (unless you pass --auto-adopt below).
#
# Copy the next line into 'crontab -e':
${MIN} ${HOUR} * * * "${RUNNER}" run --project "${PROJECT}" --scope invoked --backend ${BACKEND} >> "${PROJECT}/.skillopt-sleep/cron.log" 2>&1
#
# For fully-autonomous adoption (power users), append: --auto-adopt
# To spend real API budget for genuine lift, set BACKEND=anthropic above.
# ────────────────────────────────────────────────────────────────────────────
EOF
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#!/usr/bin/env bash
# SkillOpt-Sleep runner — invokes the skillopt.sleep engine with a suitable
# Python interpreter, from the repo that contains this plugin.
#
# Usage: sleep.sh <run|dry-run|status|adopt|harvest> [extra args...]
set -euo pipefail
# Resolve the repo root: the plugin lives at <repo>/skillopt-sleep-plugin,
# so the engine package is at <repo>/skillopt/sleep. CLAUDE_PLUGIN_ROOT points
# at the plugin dir when run by Claude Code; fall back to this script's dir.
PLUGIN_ROOT="${CLAUDE_PLUGIN_ROOT:-$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)}"
REPO_ROOT="$(cd "$PLUGIN_ROOT/.." && pwd)"
# Pick an interpreter that satisfies SkillOpt's 3.10+ requirement.
PY=""
for cand in python3.12 python3.11 python3.10 python3; do
if command -v "$cand" >/dev/null 2>&1; then
ver="$("$cand" -c 'import sys; print("%d%d" % sys.version_info[:2])' 2>/dev/null || echo 0)"
if [ "${ver:-0}" -ge 310 ]; then PY="$cand"; break; fi
fi
done
if [ -z "$PY" ]; then
echo "[sleep] ERROR: need Python >= 3.10 (found none). Install one and retry." >&2
exit 1
fi
if [ "$#" -eq 0 ]; then set -- status; fi
cd "$REPO_ROOT"
exec "$PY" -m skillopt.sleep "$@"
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---
name: skillopt-sleep
description: "Use when the user wants their Claude agent to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, memory/skill consolidation, or says things like '让 agent 越用越好用', 'review my past sessions', 'learn my preferences', 'consolidate what you learned', 'run the sleep cycle', or wants to schedule offline self-optimization. Drives the skillopt.sleep engine: harvest past sessions → mine recurring tasks → replay offline → consolidate validated CLAUDE.md/SKILL.md behind a held-out gate."
---
# SkillOpt-Sleep: offline self-evolution for a local Claude agent
SkillOpt-Sleep gives the user's agent a **sleep cycle**. While the user is
offline (e.g. nightly), it reviews their real past Claude Code sessions,
re-runs recurring tasks on their own API budget, and consolidates what it
learns into **memory** (`CLAUDE.md`) and **skills** (`SKILL.md`) — but only
keeps changes that pass a held-out validation gate, and only after the user
adopts them. The agent gets measurably better at *this* user's recurring work,
with no model-weight training. It is the deployment-time analogue of training:
short-term experience → long-term competence.
It synthesizes three ideas:
- **SkillOpt** — the skill/memory doc is trainable text; bounded add/delete/replace
edits; accepted only through a held-out gate; rejected edits become negative feedback.
- **Claude Dreams** — offline consolidation that reads past sessions and rebuilds
memory (dedup/merge/resolve); the input is never mutated; output is reviewed then adopted.
- **Agent sleep** — periodic offline replay turns episodes into durable skill.
## When to use this skill
Trigger when the user wants any of:
- "make my agent learn from how I use it" / "越用越好用" / "remember my preferences across sessions"
- a nightly/scheduled or on-demand **offline self-improvement / dream / sleep** run
- to **review past sessions/trajectories** and distill recurring tasks
- to **consolidate** feedback into `CLAUDE.md` or a managed skill
- to **schedule** the cycle (cron) or **adopt** a staged proposal
## The cycle (six stages)
1. **Harvest** — read `~/.claude/projects/*/<session>.jsonl` + `~/.claude/history.jsonl` (READ-ONLY) → session digests.
2. **Mine** — digests → `TaskRecord`s (recurring intents + outcome labels + checkable refs where possible).
3. **Replay** — re-run tasks offline under the *current* skill+memory → (hard, soft) scores.
4. **Consolidate** — reflect on failures → propose bounded edits → **gate** on a held-out slice; accept only if it strictly improves.
5. **Stage** — write `proposed_CLAUDE.md`, `proposed_SKILL.md`, a diff, and `report.md` into `<project>/.skillopt-sleep/staging/<date>/`. **Nothing live changes.**
6. **Adopt** — explicit (or opt-in auto): copy staged files over live ones, backing up first.
## How to drive it
Prefer the `/sleep` command. Under the hood it calls the bundled runner:
```bash
"${CLAUDE_PLUGIN_ROOT}/scripts/sleep.sh" status # what's happened
"${CLAUDE_PLUGIN_ROOT}/scripts/sleep.sh" dry-run --project "$(pwd)" # safe preview
"${CLAUDE_PLUGIN_ROOT}/scripts/sleep.sh" run --project "$(pwd)" # full cycle, stages a proposal
"${CLAUDE_PLUGIN_ROOT}/scripts/sleep.sh" adopt --project "$(pwd)" # apply staged proposal (with backup)
```
- Default backend is `mock` (deterministic, **no API spend**) — good for trying the plumbing.
- Add `--backend anthropic` to spend the user's real budget for genuine improvement.
- Scope defaults to the invoked project; `--scope all` harvests every project.
## Hard rules
- **Never** hand-edit the user's `CLAUDE.md` / `SKILL.md` as part of this skill.
Only the `adopt` action changes live files, and it backs them up first.
- Harvest is read-only. `mock` replay has no side effects.
- Always show the user the **held-out baseline → candidate** score and the
exact proposed edits before suggesting adoption. Evidence before adoption.
- If asked whether it really helps, run
`python -m skillopt.sleep.experiments.run_experiment --persona researcher --json`
— a deterministic demo that proves held-out lift and that the gate blocks
harmful edits.
## Validate / demo
```bash
# deterministic proof (no API): held-out score rises, gate blocks regressions
python -m skillopt.sleep.experiments.run_experiment --persona researcher --assert-improves
python -m skillopt.sleep.experiments.run_experiment --persona programmer --assert-improves
```
See `docs/sleep/experiment_results.md` for recorded output and
`docs/superpowers/specs/2026-06-07-skillopt-sleep-claude-code-plugin-design.md`
for the full design.