feat(plugins): add OpenClaw shell for SkillOpt-Sleep
Adds a thin OpenClaw shell wrapping the SkillOpt-Sleep engine. Enables nightly validation-gated skill improvement cycles for OpenClaw agents. Components: - skillopt_sleep_openclaw.py: DeepSeek V4 Pro + Ollama nomic-embed-text backend, mirroring the Claude/Codex/Copilot backend pattern. - run_sleep.py: CLI entry point supporting dry-run and pre-built task files. - run_sleep_cron.sh: bash wrapper for nightly cron invocation. - slash_sleep.py: /sleep command (status / run / adopt / reject / cost). - config.json: engine config tuned for our stack. - SKILL.md: OpenClaw skill manifest. - tests/: 14 held-out tasks across 3 categories (research-cron, devops, wiki). OpenClaw is the 4th ecosystem in which SkillOpt-Sleep can be deployed, joining Claude Code, Codex, and Copilot. The shell follows the same single-engine / thin-shell pattern as the existing three plugins. End-to-end tested: pipeline runs against real OpenClaw session transcripts, gate correctly rejects non-improvements, staging artifacts land in ~/.skillopt-sleep/staging/<night>/. Cost: ~$0.02/night on DeepSeek V4 Pro.
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# OpenClaw Plugin 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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## What it does
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Adds a nightly "sleep cycle" to any OpenClaw agent. The cycle:
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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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Nothing live changes until you adopt. Every adopt backs up first.
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## Install
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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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```
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## Use
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### Manual trigger
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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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# Dry run (report only)
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python3 ~/.openclaw/workspace/skills/skillopt-sleep/run_sleep.py --dry-run
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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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### Slash command
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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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## Architecture
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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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The OpenClaw shell is one engine (skillopt_sleep/) + one backend (DeepSeek/Ollama) + four thin wrappers (cron, slash, skill, tests).
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## Why this matters for OpenClaw
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OpenClaw currently has no built-in "self-evolving skills" mechanism. The community has:
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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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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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## Validation
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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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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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## 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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## License
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MIT (same as SkillOpt core).
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