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',

One skill from claude-skills.

shell

$ npx -y skills add alirezarezvani/claude-skills --skill skillopt-sleep --agent claude-code

Installs just this skill. Get the whole plugin for auto-invocation.

How it fires

How this skill gets triggered: by you, by Claude, or both.

Fires itselfClaude auto-loads it when your prompt matches the work.
You can call itInvoke it directly when you want it.
Slash command/skillopt-sleep

Context preview

The summary Claude sees to decide when to auto-load this skill.

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',

Stats

Stars23,056

Forks3,139

LanguagePython

LicenseMIT

Ships with claude-skills

SKILL.md

skillopt-sleep.SKILL.md

---
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 '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."
---

# 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