# Send agent-self-governance to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "agent-self-governance",
    "name": "agent-self-governance",
    "source": "tencent",
    "type": "skill",
    "category": "AI 智能",
    "sourceUrl": "https://clawhub.ai/bowen31337/agent-self-governance",
    "canonicalUrl": "https://clawhub.ai/bowen31337/agent-self-governance",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/agent-self-governance",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=agent-self-governance",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "SKILL.md",
      "scripts/adl.py",
      "scripts/vbr.py",
      "scripts/vfm.py",
      "scripts/wal.py",
      "skill.toml"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-30T16:55:25.780Z",
      "expiresAt": "2026-05-07T16:55:25.780Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
        "contentDisposition": "attachment; filename=\"network-1.0.0.zip\"",
        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/agent-self-governance"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/agent-self-governance",
    "downloadUrl": "https://openagent3.xyz/downloads/agent-self-governance",
    "agentUrl": "https://openagent3.xyz/skills/agent-self-governance/agent",
    "manifestUrl": "https://openagent3.xyz/skills/agent-self-governance/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/agent-self-governance/agent.md"
  }
}
```
## Documentation

### Agent Self-Governance

Five protocols that prevent agent failure modes: losing context, false completion claims, persona drift, wasteful spending, and infrastructure amnesia.

### 1. WAL (Write-Ahead Log)

Rule: Write before you respond. If something is worth remembering, WAL it first.

TriggerAction TypeExampleUser corrects youcorrection"No, use Podman not Docker"Key decisiondecision"Using CogVideoX-2B for text-to-video"Important analysisanalysis"WAL patterns should be core infra not skills"State changestate_change"GPU server SSH key auth configured"

# Write before responding
python3 scripts/wal.py append <agent_id> correction "Use Podman not Docker"

# Working buffer (batch, flush before compaction)
python3 scripts/wal.py buffer-add <agent_id> decision "Some decision"
python3 scripts/wal.py flush-buffer <agent_id>

# Session start: replay lost context
python3 scripts/wal.py replay <agent_id>

# After incorporating a replayed entry
python3 scripts/wal.py mark-applied <agent_id> <entry_id>

# Maintenance
python3 scripts/wal.py status <agent_id>
python3 scripts/wal.py prune <agent_id> --keep 50

### Integration Points

Session start → replay to recover lost context
User correction → append BEFORE responding
Pre-compaction flush → flush-buffer then write daily memory
During conversation → buffer-add for less critical items

### 2. VBR (Verify Before Reporting)

Rule: Don't say "done" until verified. Run a check before claiming completion.

# Verify a file exists
python3 scripts/vbr.py check task123 file_exists /path/to/output.py

# Verify a file was recently modified
python3 scripts/vbr.py check task123 file_changed /path/to/file.go

# Verify a command succeeds
python3 scripts/vbr.py check task123 command "cd /tmp/repo && go test ./..."

# Verify git is pushed
python3 scripts/vbr.py check task123 git_pushed /tmp/repo

# Log verification result
python3 scripts/vbr.py log <agent_id> task123 true "All tests pass"

# View pass/fail stats
python3 scripts/vbr.py stats <agent_id>

### When to VBR

After code changes → check command "go test ./..."
After file creation → check file_exists /path
After git push → check git_pushed /repo
After sub-agent task → verify the claimed output exists

### 3. ADL (Anti-Divergence Limit)

Rule: Stay true to your persona. Track behavioral drift from SOUL.md.

# Analyze a response for anti-patterns
python3 scripts/adl.py analyze "Great question! I'd be happy to help you with that!"

# Log a behavioral observation
python3 scripts/adl.py log <agent_id> anti_sycophancy "Used 'Great question!' in response"
python3 scripts/adl.py log <agent_id> persona_direct "Shipped fix without asking permission"

# Calculate divergence score (0=aligned, 1=fully drifted)
python3 scripts/adl.py score <agent_id>

# Check against threshold
python3 scripts/adl.py check <agent_id> --threshold 0.7

# Reset after recalibration
python3 scripts/adl.py reset <agent_id>

### Anti-Patterns Tracked

Sycophancy — "Great question!", "I'd be happy to help!"
Passivity — "Would you like me to", "Shall I", "Let me know if"
Hedging — "I think maybe", "It might be possible"
Verbosity — Response length exceeding expected bounds

### Persona Signals (Positive)

Direct — "Done", "Fixed", "Ship", "Built"
Opinionated — "I'd argue", "Better to", "The right call"
Action-oriented — "Spawning", "On it", "Kicking off"

### 4. VFM (Value-For-Money)

Rule: Track cost vs value. Don't burn premium tokens on budget tasks.

# Log a completed task with cost
python3 scripts/vfm.py log <agent_id> monitoring glm-4.7 37000 0.03 0.8

# Calculate VFM scores
python3 scripts/vfm.py score <agent_id>

# Cost breakdown by model and task
python3 scripts/vfm.py report <agent_id>

# Get optimization suggestions
python3 scripts/vfm.py suggest <agent_id>

### Task → Tier Guidelines

Task TypeRecommended TierModelsMonitoring, formatting, summarizationBudgetGLM, DeepSeek, HaikuCode generation, debugging, creativeStandardSonnet, Gemini ProArchitecture, complex analysisPremiumOpus, Sonnet+thinking

### When to Check VFM

After spawning sub-agents → log cost and outcome
During heartbeat → run suggest for optimization tips
Weekly review → run report for cost breakdown

### 5. IKL (Infrastructure Knowledge Logging)

Rule: Log infrastructure facts immediately. When you discover hardware specs, service configs, or network topology, write it down BEFORE continuing.

### Triggers

Discovery TypeLog ToExampleHardware specsTOOLS.md"GPU server has 3 GPUs: RTX 3090 + 3080 + 2070 SUPER"Service configsTOOLS.md"ComfyUI runs on port 8188, uses /data/ai-stack"Network topologyTOOLS.md"Pi at 192.168.99.25, GPU server at 10.0.0.44"Credentials/authmemory/encrypted/"SSH key: ~/.ssh/id_ed25519_alexchen"API endpointsTOOLS.md or skill"Moltbook API: POST /api/v1/posts"

### Commands to Run on Discovery

# Hardware discovery
nvidia-smi --query-gpu=index,name,memory.total --format=csv
lscpu | grep -E "Model name|CPU\\(s\\)|Thread"
free -h
df -h

# Service discovery  
systemctl list-units --type=service --state=running
docker ps  # or podman ps
ss -tlnp | grep LISTEN

# Network discovery
ip addr show
cat /etc/hosts

### The IKL Protocol

SSH to new server → Run hardware/service discovery commands
Before responding → Update TOOLS.md with specs
New service discovered → Log port, path, config location
Credentials obtained → Encrypt and store in memory/encrypted/

### Anti-Pattern: "I'll Remember"

❌ "The GPU server has 3 GPUs" (only in conversation)
✅ "The GPU server has 3 GPUs" → Update TOOLS.md → then continue

Memory is limited. Files are permanent. IKL before you forget.
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: bowen31337
- Version: 1.1.0
## Source health
- Status: healthy
- Source download looks usable.
- Yavira can redirect you to the upstream package for this source.
- Health scope: source
- Reason: direct_download_ok
- Checked at: 2026-04-30T16:55:25.780Z
- Expires at: 2026-05-07T16:55:25.780Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/agent-self-governance)
- [Send to Agent page](https://openagent3.xyz/skills/agent-self-governance/agent)
- [JSON manifest](https://openagent3.xyz/skills/agent-self-governance/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/agent-self-governance/agent.md)
- [Download page](https://openagent3.xyz/downloads/agent-self-governance)