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AC juhe-person-invest

自然人对外投资任职查询。根据姓名和身份证号（可选手机号）查询个人对外投资与任职企业，返回企业名称、法人/高管/股东关系、职务、持股比例、认缴出资、经营状态等。使用场景：用户说"对外投资"、"查任职"、"这个人在哪些公司任职"、"查股东"、"法人任职"、"个人投资企业"、"高管兼职"、"尽职调查"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 ≈ 881 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

自然人对外投资任职查询。根据姓名和身份证号（可选手机号）查询个人对外投资与任职企业，返回企业名称、法人/高管/股东关系、职务、持股比例、认缴出资、经营状态等。使用场景：用户说"对外投资"、"查任职"、"这个人在哪些公司任职"、"查股东"、"法人任职"、"个人投资企业"、"高管兼职"、"尽职调查"等。通过聚合数据（ju…

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 881 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 174: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (5 code blocks)
  • +3All 1 scripts are documented

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

External checks

ClawHub: suspicious
The skill appears to do the advertised lookup, but it handles national ID/mobile data in ways that can expose raw identifiers in logs and lacks clear consent/privacy guardrails.
LLM: suspicious (high) · 8 Sept 2026