AC bid-collection
招投标商机采集 — 监控全网公开招投标信息，按业务赛道智能筛选高价值商机线索。能力与副作用完整披露：(1) 通过 WebSearch/WebFetch 向各级政府公共资源交易平台、国企采购平台、行业招投标网站及第三方聚合平台发起出站 HTTP 请求，仅采集公开信息，不读取用户环境变量/API Key/敏感配置；(2) scan/monitor 结果默认写入本地 leads-output/bid/ 目录（HTML/JSON/Markdown/log），不静默写入其他位置；(3) monitor 子命令通过 CronCreate 创建定时任务（会修改宿主调度），周期性发起出站请求并发送 PushNotification 系统通知，需用户显式确认后才会启动；(4) add-source 子命令会向用户指定的 URL 发起出站请求，存在 SSRF 类风险，仅应添加可信平台；(5) 不读取非公开/需登录内容，不代用户投标。触发词：招投标、商机采集、招标监控、采购线索、bid-collection。Use when the user asks for 招投标商机采集、招标监控、采购线索扫描、bid-collection，或要求监控政府/国企采购平台商机。
招投标商机采集 — 监控全网公开招投标信息，按业务赛道智能筛选高价值商机线索。能力与副作用完整披露：(1) 通过 WebSearch/WebFetch 向各级政府公共资源交易平台、国企采购平台、行业招投标网站及第三方聚合平台发起出站 HTTP 请求，仅采集公开信息，不读取用户环境变量/API…
As a process C 51/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- 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: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 51/100
- 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
- 30Running it twice. 4 mutating operations with no state check
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 25 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2492 tokens
- 100Progress reporting. Reports progress
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
- -225 emoji in the instructions: noise for the model
- -43 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +3Description length 529: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 25 items
- +4Has examples (10 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.