SKILLEMALL.ai

AD bid-opportunity-advisor

投标机会顾问。当用户想判断「某个标讯/某类标讯值不值得跟、我的公司适不适合投、该报什么价、对手是谁」时使用。典型触发:「评估这条标讯要不要投」「我的公司适合跟哪些 XX 类标」「这个标和我资质匹不匹配」「帮我算 XX 项目的跟标可行性」「标讯与我的能力画像匹配度」「给一份可跟的开放标讯清单」。本技能只做分析与建议,不替用户注册账号、不采集设备指纹、不在未授权时向外发任何数据。

ClawHub Agent Skills author: 一线评标专家 v1.0.0 MIT-0 34 files body ≈ 1 208 tokens Open the sourceclawhub.ai analyzed 2 d ago

投标机会顾问。当用户想判断「某个标讯/某类标讯值不值得跟、我的公司适不适合投、该报什么价、对手是谁」时使用。典型触发:「评估这条标讯要不要投」「我的公司适合跟哪些 XX 类标」「这个标和我资质匹不匹配」「帮我算 XX…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureProcurementAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
D
46/100
Unfinished process
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: 34. 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")
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 100Steps. 40 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1208 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 189: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 40 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 5 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: clean
This skill is a disclosed bidding-analysis assistant that uses public procurement data and an optional local company profile to generate advice and reports.
LLM: benign (high) · VirusTotal: · 7 Aug 2026