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风鸟企业数据查询引擎，用于查询中国企业的结构化工商、关系与风险信息，并在需要时生成报告、摘要等衍生输出。 当用户想查询企业基本信息（如法定代表人、注册号、统一社会信用代码、成立日期、注册地址、经营范围及基础联系方式）、股东结构、主要人员、对外投资、工商变更，或查询被执行人、失信被执行人、限制高消费、经营异常、严重违法、行政处罚等风险信息时使用。 也适用于合作方背景核查、供应商管理、客户风险识别等场景。支持输入企业简称并先做模糊搜索获取企业主体。

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 14 files body ≈ 2 127 tokens Open the sourcegithub.com↗ analyzed 2 d ago

风鸟企业数据查询引擎，用于查询中国企业的结构化工商、关系与风险信息，并在需要时生成报告、摘要等衍生输出。…

As a process F 35/100 · Will not run — References files that are not bundled: references/field_definitions_*.md

ProcedureAI 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
85/100
safety, quality, tests
Safety 60%
99
Quality 40%
64
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/field_definitions_*.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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 Exfiltration net-credential-use SKILL.md:154
    Credential used in a network call (verify the destination is the intended service) (documentation table row)
    | API 鉴权失败（`code=9999`） | 检查 `FN_API_KEY`；Windows PowerShell 优先用 `$env:FN_API_KEY` 或 `Get-Item Env:FN_API_KEY -ErrorAction SilentlyContinue \| Select-Object -ExpandProperty Value` 校验，不要仅凭 `powershell
    table

Files scanned: 14. 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")
  • warning missing-ref reference to a missing file: references/field_definitions_*.md
  • note frontmatter-key unknown frontmatter key "env"
  • note frontmatter-key unknown frontmatter key "security"
  • note frontmatter-key unknown frontmatter key "auto_invoke"
  • note frontmatter-key unknown frontmatter key "examples"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/field_definitions_*.md
  • 0Tools and files. 1 referenced file(s) missing: references/field_definitions_*.md
  • 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
  • 100Steps. 45 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2127 tokens
  • 100Running it twice. No mutating operations
  • 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
  • -33 of 4 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 224: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 45 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.