Agent Skill
Skillopt Sleep skill
skillopt-sleepmicrosoft/SkillOptplugins/dsh/skills/skillopt-sleep/SKILL.md
Use when the user wants the dsh agent to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, skill/memory 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 background self-optimization. Drives the skillopt_sleep engine through the skillopt_* tools: harvest past sessions -> mine recurring tasks -> replay via a selected backend -> consolidate validated skills behind a held-out gate.
always on
127 tokname + description
once used
1,314 tokSKILL.md body
bundled files
0
repo stars
19kGitHub
Install the Skillopt Sleep skill
Skills CLI (Claude Code, Codex, Cursor and others)
npx skills add https://github.com/microsoft/SkillOpt --skill skillopt-sleep
Claude Code, by hand (all projects)
git clone --depth 1 https://github.com/microsoft/SkillOpt.git /tmp/SkillOpt mkdir -p ~/.claude/skills cp -R /tmp/SkillOpt/plugins/dsh/skills/skillopt-sleep ~/.claude/skills/skillopt-sleep
For one project only, copy the folder into .claude/skills/ in that project instead. The agent picks it up when a task matches its description.
What it costs your context
Agent Skills load in three steps. Tokens counted with the o200k tokenizer; your model's count will differ a little.
| When | What loads | Cost |
|---|---|---|
| Every session | Name and description | 127 tok |
| When the agent uses it | The SKILL.md instructions | 1,314 tok |
| Only if opened | No bundled files | — |
Until it is used, skillopt-sleep costs about 11× less than the median MCP server we measured (1,362 tokens on every turn). Installing all 5 skills from microsoft/SkillOpt would load 473 tokens of descriptions. Skills vs MCP study
Checks
Our checks found nothing to flag: it follows the Agent Skills specification's naming and size guidelines and doesn't pipe downloads into a shell.
Checked 2026-10-22 · method
What's inside
The headings of its SKILL.md. Read the full file on GitHub.
- SkillOpt-Sleep: usage-driven self-evolution for the dsh agent
- When to use
- The cycle (six stages)
- Driving it
- Parameters
- Configuration (cordis.yml / bundle patch)
- Hard rules
- Validate / demo (no API spend)
More skills from microsoft/SkillOpt
- skillopt-sleepmicrosoft/SkillOpt
Use when the user wants Cursor to learn from recent local sessions, asks for an offline sleep or dream cycle, wants to consolidate recurring work into a Cursor skill, or requests SkillOpt-Sleep status, harvest, dry-run, run, scheduling, review, or adoption. Drives the validation-gated skillopt_sleep engine with Cursor transcripts and the optional Cursor Agent CLI backend.
19k79 tok idle · 2,170 in use - skillopt-sleepmicrosoft/SkillOpt
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 background self-optimization. Drives the skillopt_sleep engine: harvest past sessions -> mine recurring tasks -> replay through a selected backend -> consolidate validated CLAUDE.md/SKILL.md behind a held-out gate.
19k127 tok idle · 2,075 in use - skillopt-sleepmicrosoft/SkillOpt
Use when the user wants Codex to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, wants Codex to review past sessions, learn preferences, consolidate memory/skills, run dry-run/run/adopt/status for SkillOpt-Sleep, or schedule background self-optimization. Drives the skillopt_sleep engine: harvest past sessions -> mine recurring tasks -> replay through a selected backend -> consolidate validated memory + skills behind a held-out gate.
19k103 tok idle · 2,249 in use - skillopt-sleepmicrosoft/SkillOpt
Reference-only OpenClaw adaptation of SkillOpt-Sleep. Use it to study or port the contributed DeepSeek wrapper, not as a ready-to-run installation.
19k437 tok idle · 1,047 in use