BD juhe-vehicle-dd-pro-a2a
车辆尽调报告 Pro（标准版）：一次付费通过车架号（VIN）查询车辆配置档案、登记五项与过户流转，输出带摘要灯的购前快检报告；付费前须确认车辆类型与是否事故（hasSg）。 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。 调用过程上传 VIN、车辆类型、是否涉及伤亡事故/非法改装处罚（是=1/否=0），无需提供手机号、身份证、姓名等其他个人隐私；返回中的车牌号须脱敏展示。 适用于二手车购前快检、核实车型配置与过户次数、金融机构/保险核对车辆基础与流转信息等场景。 注意：纯查车型配置（排量/轴距/公告号等）且无尽调/过户意图时，应使用 vin-query-a2a；纯查过户历史应使用 juhe-vehicle-owner-a2a，不要触发本技能。
车辆尽调报告 Pro（标准版）：一次付费通过车架号（VIN）查询车辆配置档案、登记五项与过户流转，输出带摘要灯的购前快检报告；付费前须确认车辆类型与是否事故（hasSg）。 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。 调用过程上传…
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: 5. 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. 110 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2388 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
- +1No license
- +2Single-language instructions
- +3Description length 358: enough signal without eating the budget
- +4Structure: 29 headings
- +3Step-by-step instructions: 110 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.