Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
agent-self-governance
Self-governance protocol for autonomous agents: WAL (Write-Ahead Log), VBR (Verify Before Reporting), ADL (Anti-Divergence Limit), and VFM (Value-For-Money)....
skill openclawclawhub Free
Self-governance protocol for autonomous agents: WAL (Write-Ahead Log), VBR (Verify Before Reporting), ADL (Anti-Divergence Limit), and VFM (Value-For-Money)....
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Known item issue.
This item's current download entry is known to bounce back to a listing or homepage instead of returning a package file.
Quick setup
- Open the source page and confirm the package flow manually.
- Review SKILL.md if you can obtain the files.
- Treat this source as manual setup until the download is verified.
Package facts
- Download mode
- Manual review
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/adl.py, scripts/vbr.py, scripts/vfm.py, scripts/wal.py, skill.toml
Validation
- Open the source listing and confirm there is a real package or setup artifact available.
- Review SKILL.md before asking your agent to continue.
- Treat this source as manual setup until the upstream download flow is fixed.
Install with your agent
Agent handoff
Use the source page and any available docs to guide the install because the item currently does not return a direct package file.
- Open the source page via Open source listing.
- If you can obtain the package, extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the source page and extracted files.
New install
I tried to install a skill package from Yavira, but the item currently does not return a direct package file. Inspect the source page and any extracted docs, then tell me what you can confirm and any manual steps still required.
Upgrade existing
I tried to upgrade a skill package from Yavira, but the item currently does not return a direct package file. Compare the source page and any extracted docs with my current installation, then summarize what changed and what manual follow-up I still need.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.1.0
Provenance
- Publisher
- bowen31337
- Source page
- View original listing
- Canonical URL
- Open canonical page
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 β replay to recover lost context User correction β append BEFORE responding Pre-compaction flush β flush-buffer then write daily memory During conversation β 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 β check command "go test ./..." After file creation β check file_exists /path After git push β check git_pushed /repo After sub-agent task β 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 β "Great question!", "I'd be happy to help!" Passivity β "Would you like me to", "Shall I", "Let me know if" Hedging β "I think maybe", "It might be possible" Verbosity β Response length exceeding expected bounds
Persona Signals (Positive)
Direct β "Done", "Fixed", "Ship", "Built" Opinionated β "I'd argue", "Better to", "The right call" Action-oriented β "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 β 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 β log cost and outcome During heartbeat β run suggest for optimization tips Weekly review β 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 β Run hardware/service discovery commands Before responding β Update TOOLS.md with specs New service discovered β Log port, path, config location Credentials obtained β Encrypt and store in memory/encrypted/
Anti-Pattern: "I'll Remember"
β "The GPU server has 3 GPUs" (only in conversation) β "The GPU server has 3 GPUs" β Update TOOLS.md β then continue Memory is limited. Files are permanent. IKL before you forget.
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Scripts1 Docs1 Files
- SKILL.md
- scripts/adl.py
- scripts/vbr.py
- scripts/vfm.py
- scripts/wal.py
- skill.toml