BD juhe-enterprise-dd-pro-a2a
企业尽调报告 Pro（标准版）：一次付费返回企业详细工商信息（基本信息、股东、主要人员、分支、变更、内嵌经营异常等），并汇总经营异常、被执行、失信、限制高消费等公开风险信号，输出带摘要灯的尽调报告。 基于 A2M（HTTP 402）收单协议。买家通过本 Skill 向卖家服务端发起请求，完成支付后获取相关结果。 调用过程仅上传查询用的企业名称或注册号/统一社会信用代码，无需提供手机号、身份证等其他个人隐私。 股东为自然人时不返回证件类型与证件号；机构股东可能返回公开的营业执照类标识。报告含法人姓名、股东、企业注册地址、信用代码等敏感公开信息，展示须最小化；若返回身份证号须脱敏展示（保留前6后4），禁止明文回显与日志落地，勿暗示已采集用户个人隐私。本技能不返回自然人住址/居住地址。 适用于合作前尽调、供应商/客户风险快检、核实企业是否存在失信/被执行/经营异常等场景。 注意：纯查工商档案（股东/法人/经营范围）且无风险尽调意图时，应使用 enterprise-details-a2a，不要触发本技能。 重要限制：风险类模块（经营异常/被执行/失信/限高）每次仅查最近一页而非全量；报告展示被执行/限高最多 15 条、失信最多 8 条，仅供参考，须向用户说明避免误会。
企业尽调报告 Pro（标准版）：一次付费返回企业详细工商信息（基本信息、股东、主要人员、分支、变更、内嵌经营异常等），并汇总经营异常、被执行、失信、限制高消费等公开风险信号，输出带摘要灯的尽调报告。 基于 A2M（HTTP 402）收单协议。买家通过本 Skill 向卖家服务端发起请求，完成支付后获取相关结果。…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription 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 (web) that frontmatter does not declare
- 100Steps. 107 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2399 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
- +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
- -45 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +3Description length 538: enough signal without eating the budget
- +4Structure: 30 headings
- +3Step-by-step instructions: 107 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.