docs: sync documentation with post-v0.2 changes
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# OpenClaw Plugin for SkillOpt-Sleep
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# OpenClaw reference adaptation for SkillOpt-Sleep
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Thin shell for running [SkillOpt-Sleep](https://github.com/microsoft/SkillOpt) on [OpenClaw](https://github.com/openclaw/openclaw).
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This directory is a contributed reference for connecting
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[SkillOpt-Sleep](https://github.com/microsoft/SkillOpt) to
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[OpenClaw](https://github.com/openclaw/openclaw) with a custom DeepSeek/Ollama
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backend.
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## What it does
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> **Reference status.** This is not one of the shared, plug-and-play
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> `skillopt_sleep` wrappers. Several scripts and the sample config contain
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> environment-specific absolute paths and assumptions from the original setup,
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> and the contributed wrapper has unresolved Python 3.10 syntax and backend
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> factory-signature gaps. The current checkout is not directly runnable; treat
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> it as porting source material, not an installation.
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Adds a nightly "sleep cycle" to any OpenClaw agent. The cycle:
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## Included components
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1. **Harvests** recent session transcripts from `~/.openclaw/agents/<name>/sessions/*.jsonl`
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2. **Mines** recurring task patterns using the optimizer LLM
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3. **Replays** each pattern with the current `SKILL.md` (baseline) and a candidate `SKILL.md` (with proposed edits)
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4. **Gates** the candidate against the held-out score (rejects regressions)
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5. **Stages** the accepted proposal in `~/.skillopt-sleep/staging/<night>/`
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6. Leaves adoption to the operator (Ethan)
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| File | Purpose |
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|---|---|
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| `run_sleep.py` | custom cycle entry point |
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| `skillopt_sleep_openclaw.py` | DeepSeek Chat Completions backend plus local Ollama embeddings |
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| `run_sleep_cron.sh` | category-oriented cron wrapper |
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| `slash_sleep.py` | experimental `/sleep` command helper |
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| `config.json` | example engine configuration |
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| `SKILL.md` | OpenClaw skill manifest |
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| `tests/*.json` | example task sets for research, DevOps, and wiki workflows |
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Nothing live changes until you adopt. Every adopt backs up first.
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The adaptation imports the shared engine but registers its own backend and
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maintains its own wrapper behavior. Changes to the shared CLI documentation do
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not automatically make every option available through these custom scripts.
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## Install
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## Intended cycle
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The plugin is a thin wrapper around the engine at `~/.openclaw/workspace/SkillOpt/skillopt_sleep/`:
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```bash
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# 1. Clone the engine (one-time)
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cd ~/.openclaw/workspace
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git clone https://github.com/microsoft/SkillOpt.git
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# 2. Install the OpenClaw skill (this folder)
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ln -s /path/to/openclaw ~/.openclaw/workspace/skills/skillopt-sleep
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# 3. Configure
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cp ~/.openclaw/workspace/skills/skillopt-sleep/config.json ~/.skillopt-sleep/config.json
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$EDITOR ~/.skillopt-sleep/config.json
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# Set backend = "openclaw-deepseek"
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# Set model = "deepseek-v4-pro" (or "deepseek-v4-flash" for budget)
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# 4. Set API key
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echo 'export DEEPSEEK_API_KEY="sk-..."' >> ~/.openclaw/.env
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# 5. Add the nightly cron
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(crontab -l 2>/dev/null; echo "0 3 * * * cd ~/.openclaw/workspace/skills/skillopt-sleep && bash run_sleep_cron.sh >> ~/.skillopt-sleep/nightly.log 2>&1") | crontab -
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```text
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harvest supported session data or load a task file
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→ replay with the current skill
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→ propose bounded edits
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→ validate the candidate on held-out tasks
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→ stage a proposal for operator review
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```
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## Use
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The intended safety boundary is manual adoption: review the generated report and
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staged files before changing a live skill.
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### Manual trigger
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## Adapt before use
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```bash
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# Run one cycle now
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python3 ~/.openclaw/workspace/skills/skillopt-sleep/run_sleep.py
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1. Clone SkillOpt into a location you control:
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# Dry run (report only)
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python3 ~/.openclaw/workspace/skills/skillopt-sleep/run_sleep.py --dry-run
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```bash
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git clone https://github.com/microsoft/SkillOpt.git
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cd SkillOpt/plugins/openclaw
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```
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# One category only
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python3 ~/.openclaw/workspace/skills/skillopt-sleep/run_sleep.py --tasks tests/research-cron-tasks.json
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```
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2. Inspect and replace the sample absolute paths in `run_sleep.py`,
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`slash_sleep.py`, `run_sleep_cron.sh`, and `config.json`. Confirm the engine
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checkout, OpenClaw workspace, state directory, skill directory, and task-file
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paths all point to isolated test locations.
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### Slash command
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3. Review `config.json`. In particular, do not assume that values such as
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`max_tokens_per_night` or `replay_mode` are enforced by this custom wrapper
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merely because they appear in the example config.
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```bash
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# In any OpenClaw session
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/sleep status
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/sleep run
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/sleep run research-cron
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/sleep dry-run
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/sleep adopt # adopt most recent accepted proposal
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/sleep reject # discard most recent
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/sleep cost
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```
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4. Supply credentials through your normal secret-management mechanism. Do not
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commit a DeepSeek key or place it in a world-readable file.
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## Architecture
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5. Resolve every known porting gap listed in [`SKILL.md`](SKILL.md), add
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isolated tests for your adapted backend, and verify that `--help` imports
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cleanly on Python 3.10+. Only then start with a dry run and one reviewed
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task file. The target command should be shaped like:
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```
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plugins/openclaw/
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├── README.md # this file
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├── run_sleep_cron.sh # wrapper for cron invocation
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├── run_sleep.py # main entry point
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├── slash_sleep.py # /sleep command implementation
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├── skillopt_sleep_openclaw.py # DeepSeek + Ollama backend
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├── config.json # engine config
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├── SKILL.md # OpenClaw skill manifest
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└── tests/ # held-out test sets
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├── research-cron-tasks.json
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├── devops-tasks.json
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└── wiki-tasks.json
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```
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```bash
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cd /path/to/SkillOpt/plugins/openclaw
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python3 run_sleep.py --config /path/to/reviewed-config.json \
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--tasks tests/research-cron-tasks.json --dry-run
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```
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The OpenClaw shell is one engine (skillopt_sleep/) + one backend (DeepSeek/Ollama) + four thin wrappers (cron, slash, skill, tests).
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6. Inspect the report, paths, network destinations, and proposed edits before
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considering a non-dry run or scheduling.
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## Why this matters for OpenClaw
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## Data boundary
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OpenClaw currently has no built-in "self-evolving skills" mechanism. The community has:
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The custom `openclaw-deepseek` backend sends task, skill, response, rubric, and
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reflection content to the configured DeepSeek endpoint. Its embedding helper can
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send truncated text to the configured local Ollama service. Do not assume these
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outbound prompts have been fully redacted; inspect transcript/task inputs and the
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provider's retention policy before using real data.
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- **Manual skills** — Ethan writes them
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- **LLM-generated skills** — one-shot, no validation
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- **Self-revision** — unbounded, no quality bar
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Use HTTPS for a remote DeepSeek-compatible endpoint. Keep any plaintext Ollama
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endpoint on a trusted loopback interface. For a network-free engine smoke test,
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use the shared SkillOpt-Sleep CLI with `--backend mock` rather than assuming this
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custom wrapper is isolated.
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SkillOpt-Sleep adds a 4th option: **validated self-evolution**. The skill is the training target, the engine is the optimizer, the gate is the quality bar, the operator is the human-in-the-loop.
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## Scheduling
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## Validation
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`run_sleep_cron.sh` and the scheduling helpers are examples, not portable
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installers. Adapt their paths, create log directories, verify their environment,
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and run the exact command manually before adding a cron entry. Scheduled runs
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must preserve the same manual-adoption and credential boundaries as interactive
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runs.
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Validated on the public [gbrain-evals](https://github.com/garrytan/gbrain-evals) `skillopt-v1` benchmark with real Claude and Codex (deficient skills 0.00 → 1.00 on held-out, all 4 seeds).
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## Validation scope
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End-to-end test on our own 14-task held-out set: pipeline runs, gate correctly rejects non-improvements, staging artifacts land in `~/.skillopt-sleep/staging/<night>/`.
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The bundled JSON files are example held-out task sets, not a universal OpenClaw
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benchmark. Provider cost and quality depend on the selected model, task content,
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number of calls, and pricing at run time; this reference does not promise a fixed
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nightly cost. Validate the adapted workflow in an isolated workspace before
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using it on live skills.
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## Cost
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Measured: ~$0.02/night with `deepseek-v4-pro` at 12 tasks/night. ~$0.59/month, $7.18/year.
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For the supported shared-engine CLI and its current flags, see the
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[integration reference](../README.md#supported-cli-surface). For measured
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SkillOpt-Sleep results and limitations, see
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[`docs/sleep/RESULTS.md`](../../docs/sleep/RESULTS.md).
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## License
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MIT (same as SkillOpt core).
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MIT, consistent with SkillOpt core.
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