BF gp-rejection-decision-support
政府采购评审（评标委员会专家）侧无效投标/废标决策支持引擎。当用户提供"某投标人的具体响应情况 + 采购文件对应条款"并询问"该不该认定无效投标""应当无效还是澄清补正""帮我写评标报告用的无效投标理由"时触发。输出三类成果：① 是否构成无效投标的判断及法条/条款依据；② 应当无效与可澄清补正的区分判定（避免把可补正的形式瑕疵直接认定无效，或把实质偏差误当可澄清）；③ 可直接写入评标报告的规范化无效投标理由措辞。核心目标：评得准、无效得有依据、经得起质疑投诉复核、不踩纪律红线。区别于"政采无效投标风险雷达"（扫描采购文件提取风险条款）、"政府采购问答引擎"（通用政采问答）。
政府采购评审（评标委员会专家）侧无效投标/废标决策支持引擎。当用户提供"某投标人的具体响应情况 + 采购文件对应条款"并询问"该不该认定无效投标""应当无效还是澄清补正""帮我写评标报告用的无效投标理由"时触发。输出三类成果：① 是否构成无效投标的判断及法条/条款依据；②…
As a process F 35/100 · Will not run — References files that are not bundled: references/decision_framework.md, references/kb_mounting.md, references/discipline_redlines.md
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: references/decision_framework.md - warning
missing-refreference to a missing file: references/kb_mounting.md - warning
missing-refreference to a missing file: references/discipline_redlines.md - warning
missing-refreference to a missing file: references/rejection_wording_templates.md - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 35/100
- 0Tools and files. 4 referenced file(s) missing: references/decision_framework.md, references/kb_mounting.md, references/discipline_redlines.md
- 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. 32 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1153 tokens
- 100Running it twice. No mutating operations
- low 11 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 tags): a typed call is more reliable
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
- +1No license
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +3Description length 290: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.