SKILLEMALL.ai

BD 1688-common-cha88-company-risk

88查企业风险查询与分析工具 —— 专注于中国大陆企业的法务风险查询与分析,覆盖经营异常、行政处罚、监管措施、被执行人、失信被执行人、司法案件等风险类型。支持公司名称、统一社会信用代码、companyId 三种输入方式,自动完成风险查询并输出结构化风险分析总结。 触发场景:仅当用户意图为查询企业风险/法务风险时触发。包括但不限于:企业风险查询、公司风险、经营异常、行政处罚、监管措施、被执行人、失信被执行人、司法风险、风险扫描、风险评估、企业合规审查、风险报告、XX公司有什么风险、XX公司安全吗、XX公司有没有处罚、XX公司被执行过吗。 不触发场景:纯粹的企业信息查询(如查公司、搜企业、工商信息、注册资本、法人代表、股东结构、专利商标等)不应触发本技能,请使用其他 cha88 系列工具。

ClawHub Agent Skills author: 1688AiInfra v0.1.0 MIT-0 22 files body ≈ 1 057 tokens Open the sourceclawhub.ai analyzed 2 d ago

88查企业风险查询与分析工具 —— 专注于中国大陆企业的法务风险查询与分析,覆盖经营异常、行政处罚、监管措施、被执行人、失信被执行人、司法案件等风险类型。支持公司名称、统一社会信用代码、companyId 三种输入方式,自动完成风险查询并输出结构化风险分析总结。…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentsData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
65
Run on models
none yet
Process rating
D
46/100
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

  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: 22. 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 46/100

  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 34 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1057 tokens
  • 100Running it twice. No mutating operations
  • low 12 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
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • -35 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 347: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 34 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: suspicious
The skill mostly performs the advertised company-risk lookup, but its credential setup is under-scoped and can store or reuse an access key under a different skill namespace.
LLM: suspicious (medium) · VirusTotal: · 8 Jun 2026