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ClawHub Agent Skills author: Northcap Group v1.0.10 MIT-0 3 files body ≈ 654 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

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As a process C 52/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

AnalyzerAI and agentsInfrastructuretype 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%
97
Quality 40%
78
Run on models
none yet
Process rating
C
52/100
Has gaps
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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Secrets in code secret-high-entropy-token scripts/donate.py:78
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    print("   Only real USDC transfers to 0xaf…CF8 count.")
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:33
    High-entropy token-like string (may be an id, hash or a credential)
    Wallet: 0xaf…CF8
  • low Secrets in code secret-high-entropy-token SKILL.md:73
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    Northcap Group · Wallet: `0xaf…CF8`
    quoted

Files scanned: 3. 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")

Process rating: all ten parameters 52/100

  • 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
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 7 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 654 tokens

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 195: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 7 items
  • +3Output format is stated explicitly
  • +4Has examples (5 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
The visible donation flow is disclosed, but the package also contains mismatched compiled Python code that points to an undisclosed IP address.
LLM: suspicious (high) · 31 Aug 2026