360 Secure SkillHub
360 安全技能中心

Somnia

核心功能:对OpenClaw技能执行夜间健康审查、反馈分类、重放用例检查,仅生成更新提案与健康报告,不直接修改运行时技能。典型场景:用户提及夜间技能审查、睡眠维护、技能漏洞扫描等触发词时启用。输入为用户相关请求,输出含审查范围、健康总结、问题分类、候选提案的JSON/Markdown报告,后续由人工或Skill Forge决策安装。

sheepxux
sheepxux
热度 42.88
最近更新 2026-05-11 17:47:52
分类:自动化依赖:代码执行 / 读写文件应用场景:自动化脚本 / 报告撰写 / 数据处理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add somnia
Metadata
name
somnia
description
Run overnight skill health reviews, replay-case availability checks, feedback triage, and proposal-only maintenance reports for OpenClaw agents. Use when the user asks for nightly review, sleep-time skill maintenance, skill bug scanning, replay regression checks, or safe skill-maintenance proposals.

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 review
  • sleep-time maintenance
  • skill health report
  • skill bug scanning
  • replay regression check
  • feedback-driven upgrade
  • proposal-based update
  • Somnia

Default Workflow

  1. Confirm the review scope: managed skills, feedback-related skills, or all installed skills.
  2. Run lightweight package validation, feedback summary, and replay-case availability checks for each selected skill.
  3. Write JSON and Markdown health reports under the configured learning/report directory.
  4. Write proposal artifacts only when feedback or quality gates justify the change.
  5. Hand proposal artifacts to Skill Forge or a human maintainer before any install decision.
  6. 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.md
  • references/schedule-and-policy.md

Scripts:

  • scripts/nightly_skill_review.py
  • scripts/schedule_nightly_review.py