SKILLEMALL.ai

AC contract-risk-review-claw

合同风险审查虾 — 深度识别合同风险条款,给出修订建议,守住法律红线。 **当以下情况时使用此 Skill**: (1) 用户上传合同文件(PDF/Word/文本),要求审查风险 (2) 需要识别不平等条款、违约责任失衡、知识产权陷阱、管辖权不利等风险 (3) 需要对比我方模板与对方合同,找出被修改的关键条款 (4) 需要批量扫描历史合同库,找出高风险合同 (5) 需要生成结构化审查报告(风险清单 + 修订建议) (6) 用户提到"合同审查"、"风险识别"、"条款审核"、"合同风险"、"法律审查"、"不平等条款"、"违约责任"、"知识产权"、"管辖权"、"合同修订"、"帮我看看这份合同"、"这份合同有没有坑"

ClawHub Agent Skills author: Ricky v1.0.0 MIT-0 6 files body ≈ 395 tokens Open the sourceclawhub.ai analyzed 4 d ago

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

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
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: 6. 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. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 395 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
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 309: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This is a Chinese contract-review guidance skill made of markdown reference files, with no hidden code or automatic data transfer found.
LLM: benign (high) · VirusTotal: · 29 May 2026