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ClawHub Agent Skills author: Fried_Avocado v1.3.1 MIT-0 11 files body ≈ 2 125 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 64/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

GeneratorGitHubInfrastructuretype 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
87/100
safety, quality, tests
Safety 60%
98
Quality 40%
70
Run on models
none yet
Process rating
C
64/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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 Dangerous commands cmd-privilege scripts/md_to_png.js:107
    Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
    args: ['--no-sandbox', '--disable-setuid-sandbox']
    detectorcode literal
  • low Dangerous commands cmd-privilege scripts/md_to_png.js:460
    Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
    args: ['--no-sandbox', '--disable-setuid-sandbox'],
    detectorcode literal

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "emoji"

Process rating: all ten parameters 64/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 6 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. No external tools needed
  • 100Steps. 84 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2125 tokens
  • low 13 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)
  • -255 emoji in the instructions: noise for the model
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 211: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 84 items
  • +3Output format is stated explicitly
  • +4Has examples (5 code blocks)
  • +1License stated

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

External checks

ClawHub: suspicious
This is a real Markdown-to-image converter, but it needs review because it can render untrusted Markdown in a browser, make outbound requests, and leave user content on disk more broadly than its privacy claims suggest.
LLM: suspicious (high) · VirusTotal: · 29 May 2026