Quick overview
Five protocols that address common agent failure modes: WAL persists context before LLM compaction, VBR prevents false task-complete claims, ADL tracks persona drift, VFM monitors token cost against task value, and IKL captures infrastructure facts before they leave context. Each protocol has its own Python script, defined triggers, and log format.
Rather than relying on agent memory or ad-hoc notes, each failure mode gets a dedicated scriptable protocol with explicit triggers, commands, and log formats that survive context resets.
Common tasks
- Recovering key decisions after LLM context compaction mid-session
- Catching false task-complete claims before they reach the user
- Routing monitoring tasks to budget models instead of burning Opus tokens on simple summarization
- Logging GPU server specs discovered during SSH setup before they drop out of context
- Detecting sycophantic drift in agent responses over long sessions
Install paths
Primary command
openclaw install bowen31337/agent-self-governance
ClawHub installer
npx clawhub@latest install bowen31337/agent-self-governance
OpenClaw CLI
openclaw skills install bowen31337/agent-self-governance
Direct OpenClaw install
openclaw install bowen31337/agent-self-governance
Skill metadata
- Category: DevOps & Cloud
- Language: Markdown
- Version: 1.1.0
- Security status: Suspicious
Review upstream source
The full public SKILL.md body is not directly fetchable for this entry right now, so this page is using the best available catalog metadata. Review the upstream source page for the latest files, version history, and security scan details: https://clawhub.ai/bowen31337/agent-self-governance
