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BF openclaw-agent-governance

Set up or audit an OpenClaw agent workspace with standardized governance files. Use when: (1) creating a new agent workspace, (2) auditing existing agent files for compliance with governance standards, (3) onboarding a new agent, (4) user asks to set up or audit agent files. Creates/verifies: MEMORY.md (4-layer index), AGENTS.md (standard sections + agent-specific), memory/projects.md (Projects.md template), memory/lessons.md (Lessons template), memory/YYYY-MM-DD.md (daily log).

ClawHub Agent Skills author: u0003-yxuan v1.0.0 MIT-0 2 files body ≈ 710 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 37/100 · Will not run — References files that are not bundled: references/MEMORY.md.template, references/AGENTS.md.template, references/projects.md.template

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
F
37/100
Will not run
References files that are not bundled: references/MEMORY.md.template, references/AGENTS.md.template, references/projects.md.template
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/MEMORY.md.template
  • warning missing-ref reference to a missing file: references/AGENTS.md.template
  • warning missing-ref reference to a missing file: references/projects.md.template
  • warning missing-ref reference to a missing file: references/lessons.md.template
  • warning missing-ref reference to a missing file: references/daily-log.md.template

Process rating: all ten parameters 37/100

Will not run. References files that are not bundled: references/MEMORY.md.template, references/AGENTS.md.template, references/projects.md.template
  • 0Tools and files. 5 referenced file(s) missing: references/MEMORY.md.template, references/AGENTS.md.template, references/projects.md.template
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 100Steps. 26 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 710 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 485: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 26 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: clean
This skill is a disclosed workspace governance helper that creates or checks agent memory and instruction files, with no evidence of hidden code, credential use, network access, or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026