skillopt-sleep

原文涵盖的主题

• SkillOpt-Sleep: offline self-evolution for a local Claude agent
• When to use this skill
• The cycle (six stages)
• How to drive it
• Scheduling
• All CLI flags
• Config keys (/.skillopt-sleep/config.json)
• Memory consolidation

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. Trigger when the user wants any of: "make my agent learn from how I use it" / "get better the more I use it" / "remember my preferences across sessions" a nightly/scheduled or on-demand offline self-improvem

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