SKILLEMALL.ai

AC bid-doc-interpreter

招标文件拆分解读。当用户上传招标文件(PDF/DOCX/图片/多文件)并表达"解读招标文件""拆解招标文件""分析招标文件""标书解读""招标文件分析""提取招标文件关键信息""招标文件要点梳理""看看这个标有什么坑"等意图时触发。按7大模块(项目基本信息、资格性审查、符合性审查、商务要求、技术要求、废标项、评标办法与评分标准)+倾向性与排他性审查,结构化解读并输出标准化表格+要点清单+风险提示。不适用于合同审查、投标文件编制、评分/中标模拟预测、投标报价计算、质疑函/投诉书撰写——遇到此类请求应礼貌说明范围并引导至对应技能,不强行作答。

ClawHub Agent Skills author: 一线评标专家 v1.0.0 MIT-0 7 files body ≈ 1 658 tokens Open the sourceclawhub.ai analyzed 2 d ago

招标文件拆分解读。当用户上传招标文件(PDF/DOCX/图片/多文件)并表达"解读招标文件""拆解招标文件""分析招标文件""标书解读""招标文件分析""提取招标文件关键信息""招标文件要点梳理""看看这个标有什么坑"等意图时触发。按7大模块(项目基本信息、资格性审查、符合性审查、商务要求、技术要求、废标项、评标办法…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWordProcurementtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • 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-when description does not say WHEN to use the skill (no "use when")

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. No external tools needed
  • 100Steps. 33 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1658 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -224 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 7 example trigger phrases
  • +3Description length 272: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 33 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This is a disclosed bid-document analysis skill with no executable code or hidden data transfer, though it always appends an author and WeChat feedback footer to final reports.
LLM: benign (high) · VirusTotal: · 24 Jul 2026