Somnia
Overview
Somnia is the sleep-cycle maintenance layer for OpenClaw skills. It provides a repeatable review workflow that checks installed skills during quiet hours, summarizes health risks, and writes proposal artifacts without silently mutating runtime skills.
Current version: v0.4.3 "Standalone Safety".
Trigger Cues
Use this skill when the user mentions:
nightly skill reviewsleep-time maintenanceskill health reportskill bug scanningreplay regression checkfeedback-driven upgradeproposal-based updateSomnia
Default Workflow
- Confirm the review scope: managed skills, feedback-related skills, or all installed skills.
- Run lightweight package validation, feedback summary, and replay-case availability checks for each selected skill.
- Write JSON and Markdown health reports under the configured learning/report directory.
- Write proposal artifacts only when feedback or quality gates justify the change.
- Hand proposal artifacts to Skill Forge or a human maintainer before any install decision.
- Keep simulated evaluation details hidden from user-facing reports.
Output Contract
The final answer or artifact should include:
- Review scope and schedule assumption
- Skills checked and health summary
- Issues found, grouped by skill
- Update candidates proposed or blocked
- Replay and hidden-evaluation pass/fail summary
- Next action: no-op, review proposal, approve install, or adjust schedule
Quality Gates
- Never auto-install skill changes; Somnia writes proposals and reports only.
- Keep hidden evaluation and replay case details out of user-facing Telegram reports.
- Redact feedback-derived content before it becomes a replay case or report item.
- Prefer proposal files and manifests over direct mutation of installed skills.
- Keep Somnia self-contained; do not execute out-of-package Skill Forge code.
Resources
References:
references/somnia-architecture.mdreferences/schedule-and-policy.md
Scripts:
scripts/nightly_skill_review.pyscripts/schedule_nightly_review.py