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Search Beepack for reusable API packages before coding. Saves tokens and time by reusing production-tested code instead of writing from scratch.

ClawHub Agent Skills author: Guillaume De Laroque v1.0.1 MIT-0 2 files body ≈ 951 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmentInfrastructuretype 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
88/100
safety, quality, tests
Safety 60%
99
Quality 40%
71
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Risky intent intent-offensive-security SKILL.md:105
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    All packages are scanned through a 3-layer security pipeline (static analysis, LLM evaluation, community reports). Do NOT include `eval()`, `child_process`, credential harvesting, or obfuscated code i

Files scanned: 2. 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 "homepage"

Process rating: all ten parameters 56/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 40Consistency. Frontmatter name (beepack) differs from the folder (beepack-registry)
  • 70Failures and branches. 5 branches
  • 100Tools and files. No external tools needed
  • 100Steps. 38 steps
  • 100Execution cost. Instruction body is 951 tokens
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • high The skill tells the model to perform an irreversible action with no human approval

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 144: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 38 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: clean
This skill appears to be a disclosed Beepack package-discovery helper, but users should be careful about what project details they send to the external service.
LLM: benign (medium) · VirusTotal: · 29 May 2026