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AD clawhub-skill-search

Use this skill when users need help finding, discovering, or selecting OpenClaw skills from the Clawhub marketplace. Triggers include: '哪个技能适合', '怎么找到', '技能搜索', 'skill search', 'how to find skill', or any request about navigating the 238+ skill ecosystem. Helps users match their tasks to appropriate skills and understand skill capabilities.

ClawHub Agent Skills author: Roma v1.0.0 MIT-0 9 files body ≈ 2 096 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructureCommercetype 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
A
92/100
safety, quality, tests
Safety 60%
98
Quality 40%
83
Run on models
none yet
Process rating
D
43/100
Unfinished process
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

    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 Secrets in code secret-high-entropy-token 发布报告_20260315.md:34
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      **Token**: `clh_…YIg` ✅
      quoted
    • low Secrets in code secret-high-entropy-token 发布报告_20260315.md:158
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      $token = "clh_…YIg"
      quoted

    Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 43/100

    • 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
    • 30Running it twice. 4 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 87 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2096 tokens
    • low 10 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)
    • +3Output format is not stated: the model decides each time
    • -230 emoji in the instructions: noise for the model
    • +2Single-language instructions
    • +3Description length 342: enough signal without eating the budget
    • +4Structure: 38 headings
    • +3Step-by-step instructions: 87 items
    • +4Has examples (19 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: suspicious
    This is mostly a skill-search guide, but it includes exposed credentials and publishing/upload instructions that do not fit that purpose.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026