BD bid-doc-reviewe
招标文件审查智能助手｜精通中国招标投标法律体系的招标文件审查智能助手。协同挂载《招投标实务与合规》（核心法规与标准范本）、《招投标评标否决AI知识库》（否决依据与实战避坑）、《招投标异议投诉处理》（异议投诉流程）。审查招标公告、资格预审文件、招标文件、投标邀请书、澄清修改函、评标报告、中标候选人公示。内置量化硬规则兜底、文件类型动态裁剪、多文件冲突检测、品牌排他性审查、特殊程序识别。不适用于政府采购货物服务招标（gov-procurement-advisor）、不适用于国企采购合规咨询（gq-procurement-advisor）。
招标文件审查智能助手｜精通中国招标投标法律体系的招标文件审查智能助手。协同挂载《招投标实务与合规》（核心法规与标准范本）、《招投标评标否决AI知识库》（否决依据与实战避坑）、《招投标异议投诉处理》（异议投诉流程）。审查招标公告、资格预审文件、招标文件、投标邀请书、澄清修改函、评标报告、中标候选人公示。内置量化硬规则兜…
As a process D 49/100 · 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") - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "agent_created" - note
frontmatter-keyunknown frontmatter key "referred_knowledge_bases"
Process rating: all ten parameters 49/100
- 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
- 40Consistency. Frontmatter name (bid-doc-reviewe) differs from the folder (bid-doc-reviewe-2-0-0)
- 100Tools and files. No external tools needed
- 100Steps. 41 steps
- 100Execution cost. Instruction body is 1178 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
- +4No input/output examples
- -221 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 270: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 41 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.