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BD Skill Auditor 🔍

Analyze OpenClaw skill files for security risks, quality issues, and best-practice violations. Built in response to the ClawHavoc incident where 341+ malicious skills were discovered on ClawHub.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 1 105 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Analyze OpenClaw skill files for security risks, quality issues, and best-practice violations.

As a process D 47/100 · Unfinished process — weak spots: when it triggers, inputs and preconditions, failures and branches

AnalyzerData and analyticsInfrastructuretype 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
86/100
safety, quality, tests
Safety 60%
98
Quality 40%
68
Run on models
none yet
Process rating
D
47/100
Unfinished process
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Risky intent intent-offensive-security SKILL.md:26
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - 🔴 Credential harvesting (requesting API keys, tokens, passwords unnecessarily)
  • low Risky intent intent-offensive-security SKILL.md:28
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - 🔴 Privilege escalation (requesting elevated permissions, sudo usage, system modifications)

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 47/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (Skill Auditor 🔍) differs from the folder (claw1-skill-auditor)
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 30 steps
  • 100Execution cost. Instruction body is 1105 tokens
  • low 11 top-level sections: this looks like several domains in one skill

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)
  • -215 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 194: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 30 items
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.