BF enterprise-due-diligence-shuidixinyong
企业尽职调查助手（招投标视角轻尽调，习惯用水滴信用等平台看企业信用的用户适用）。当用户给出一个公司主体，想在合作/签约/账期决策前做尽职调查、信用了解、风险排查时，必须使用此SKILL：企业尽调、轻尽调、合作方审查、客户背景调查、经营实态核验（是否真实有业务）、履约能力评估、大客户依赖度分析、公开涉诉与行政处罚检索。基于全网招投标数据输出报告：经营活跃度用中标记录证明、客户供应商是真实合同关系、竞对从投标重叠算出，公开风险逐条附来源链接。支持单公司深度报告与双公司对比。即使用户没有提到「尽调」，只要想在合作前搞清楚一家公司靠不靠谱、有没有真实业务，都应使用本SKILL。注意边界：若用户给出一个具体的招标项目做该不该投的决策分析，使用 zlbx-bid-decision SKILL；若用户想主动挖掘商机/销售线索，使用 zlbx-opportunity-radar SKILL；若用户只是搜索/查询招中标公告数据，使用 zlbx-bidding SKILL。
企业尽职调查助手（招投标视角轻尽调，习惯用水滴信用等平台看企业信用的用户适用）。当用户给出一个公司主体，想在合作/签约/账期决策前做尽职调查、信用了解、风险排查时，必须使用此SKILL：企业尽调、轻尽调、合作方审查、客户背景调查、经营实态核验（是否真实有业务）、履约能力评估、大客户依赖度分析、公开涉诉与行政处罚检索。…
As a process F 35/100 · Will not run — References files that are not bundled: scripts/render_report.py
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 0. 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") - warning
missing-refreference to a missing file: scripts/render_report.py
Process rating: all ten parameters 35/100
- 0Tools and files. 1 referenced file(s) missing: scripts/render_report.py
- 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. 40 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1987 tokens
- 100Running it twice. No mutating operations
- low 13 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
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +3Description length 433: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 40 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.