AC enterprise-customer-profile-analysis
围绕目标企业的客户结构、客户行业分布、客户区域分布、客户类型特征、合作稳定性、客户价值层级 及拓展方向等维度，依托公开合规信息，搭建覆盖“客户来源—客户类型—行业分布—区域分布—合作关系— 客户价值—结构风险—拓展建议”的完整客户画像分析体系。本技能核心解决“企业核心客户群体、客户行业 与区域集中度、客户质量等级、客户结构健康度、未来高价值客户拓展方向”等关键问题。当用户需要分析 企业核心客户、研究客户画像特征、研判客户行业区域分布、评估客户质量与稳定性、分析客户集中度风险、 研究市场拓展方向、开展企业商业尽调或支撑企业投资价值评估时，激活此技能。
围绕目标企业的客户结构、客户行业分布、客户区域分布、客户类型特征、合作稳定性、客户价值层级 及拓展方向等维度，依托公开合规信息，搭建覆盖“客户来源—客户类型—行业分布—区域分布—合作关系— 客户价值—结构风险—拓展建议”的完整客户画像分析体系。本技能核心解决“企业核心客户群体、客户行业…
As a process C 53/100 · Has gaps — 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: 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") - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "triggers" - note
frontmatter-keyunknown frontmatter key "parameters" - note
frontmatter-keyunknown frontmatter key "tools"
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. Tools declared in frontmatter
- 100Steps. 121 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1763 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 277: enough signal without eating the budget
- +4Structure: 38 headings
- +3Step-by-step instructions: 121 items
- +4Has examples (1 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.