Individual skill
skillopt-sleep
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 'make my agent better the more I use it', '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 and SKILL.md behind a held-out gate.
engineering/skillopt-sleep/skills/skillopt-sleep/SKILL.md
Source commit 8f082544116fc0d014188e521ca40304cdfc86b0
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 10, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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Repository context
- Repository stars (not skill ratings)
- 29,647
- Repository last updated
- Nov 11, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agentic-ai Repository topic
- anthropic-claude Repository topic
- claude-ai Repository topic
- claude-code Repository topic
- claude-skills Repository topic
- claude-code-skills Repository topic
- ai-coding-agent Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- openai-codex Repository topic
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Read excerpt
# 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.