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AC juhe-enterprise-executed

企业被执行人信息查询（公示中及历史）。根据企业名称、统一社会信用代码、工商注册号或关键词查询被执行案件，返回案号、执行法院、执行标的、立案时间、案件状态。使用场景：用户说"被执行人"、"被执行"、"查执行案件"、"这家公司有没有被法院执行"、"执行标的"、"公示中被执行"、"历史被执行"等。通过聚合数据（juhe.cn）API 实时查询。

ClawHub Agent Skills author: juhe-skills v1.0.0 MIT-0 3 files body ≈ 965 tokens Open the sourceclawhub.ai↗ analyzed 34 h ago

企业被执行人信息查询（公示中及历史）。根据企业名称、统一社会信用代码、工商注册号或关键词查询被执行案件，返回案号、执行法院、执行标的、立案时间、案件状态。使用场景：用户说"被执行人"、"被执行"、"查执行案件"、"这家公司有没有被法院执行"、"执行标的"、"公示中被执行"、"历史被执行"等。通过聚合数据（juhe.c…

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

IntegrationSoftware developmenttype 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%
100
Quality 40%
79
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 · 0

✓ No critical or high findings

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")
  • note frontmatter-key unknown frontmatter key "homepage"

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 965 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

  • +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
  • +5Description quotes 2 example trigger phrases
  • +3Description length 170: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (6 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
This appears to be a real Juhe enterprise legal-record lookup skill, but it needs Review because it encourages risky API-key handling for a paid sensitive-data service.
LLM: suspicious (medium) · 8 Sept 2026