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一个交互式 CLI 工具，帮助开发者按分类浏览、空格多选、一键批量安装/同步 AI Agent skills 到多个编辑器。

ClawHub Agent Skills author: Jonny Looma v2.0.1 MIT-0 80 files body ≈ 93 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI 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
79/100
safety, quality, tests
Safety 60%
90
Quality 40%
63
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 · 10

✓ No critical or high findings

Medium and low: 10
  • low Secrets in code secret-high-entropy-token package-lock.json:240
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…l1I+R1H7…G3i/cYFJ…fIw==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:274
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…XcW+/GvMN…kxZ/opySAZMrc+9LY/WyjA…InQ==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:291
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…qEP+UeRV…fdw==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:325
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…Fnw/+3lVx…cQS+Yu6w==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:427
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…UzV+AA46…P4O+ng17CA==",
    detector
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:121
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…l1I+R1H7…G3i/cYFJ…fIw==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:133
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…XcW+/GvMN…kxZ/opySAZMrc+9LY/WyjA…InQ==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:139
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…qEP+UeRV…fdw==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:151
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…Fnw/+3lVx…cQS+Yu6w==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:187
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…UzV+AA46…P4O+ng17CA==}

Files scanned: 60. 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 53/100

  • 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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Steps. 14 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 93 tokens
  • 100Running it twice. No mutating operations

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)
  • +3Description length 62: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -44 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Structure: 4 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (2 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This is a real skill installer, but it can change agent/editor configuration broadly and clean up files without enough per-action safeguards.
LLM: suspicious (high) · VirusTotal: · 29 May 2026