SKILLEMALL.ai

BF bid-rejection-minefield-checker

服务于投标人——输入单一省份+行业+采购方式,基于历史否决案例库输出可打印的条款级雷区体检报告(含当前文件定位、血槽证据、风险等级、封标前自查表)。路径B支持双输入源分流(完整招标文件 / 否决记录·评标报告),雷区分型固化(竞争性淘汰不计入雷区命中)。触发词:雷区体检/否决雷区/废标风险扫描/条款级风险/投标体检报告/双路比对/双输入源。

ClawHub Agent Skills author: 一线评标专家 v1.0.0 MIT-0 7 files body ≈ 2 621 tokens Open the sourceclawhub.ai analyzed 3 d ago

服务于投标人——输入单一省份+行业+采购方式,基于历史否决案例库输出可打印的条款级雷区体检报告(含当前文件定位、血槽证据、风险等级、封标前自查表)。路径B支持双输入源分流(完整招标文件 /…

As a process F 35/100 · Will not run — References files that are not bundled: 链接, 原文链接

ProcedureProcurementtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
59
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: 链接, 原文链接
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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: 7. 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")
  • warning missing-ref reference to a missing file: 链接
  • warning missing-ref reference to a missing file: 原文链接

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: 链接, 原文链接
  • 0Tools and files. 2 referenced file(s) missing: 链接, 原文链接
  • 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. 82 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2621 tokens
  • 100Running it twice. No mutating operations
  • low 12 top-level sections: this looks like several domains in one skill

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
  • -42 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 171: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 82 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.

External checks

ClawHub: clean
This skill is a disclosed procurement-risk report generator that uses scoped knowledge-base lookups and optional user-provided documents, with no hidden execution or automatic data collection found.
LLM: benign (high) · VirusTotal: · 27 Jul 2026