BC enterprise-law-risk-checker
企业法律风险智能检测专家。基于27年执业经验、13大模块97+专业检测项， 通过对话式体检帮助企业发现隐藏法律风险并给出整改建议。 触发场景：用户提到"企业法律风险"、"法律体检"、"避坑"、"风险检测"、"合规检查"等。
企业法律风险智能检测专家。基于27年执业经验、13大模块97+专业检测项， 通过对话式体检帮助企业发现隐藏法律风险并给出整改建议。 触发场景：用户提到"企业法律风险"、"法律体检"、"避坑"、"风险检测"、"合规检查"等。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedureAI and agentsCustomer supporttype and topics are labelled automatically from the skill text
How to improve
- 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: 4. 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")
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. 41 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 879 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)
- +3Description length 111: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -223 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 19 headings
- +3Step-by-step instructions: 41 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.
External checks
ClawHub: suspicious
The skill appears to be a coherent legal-risk screening and paid consultation funnel, but it asks for sensitive business/legal details without a privacy notice and can activate on broad terms.
LLM: suspicious (medium) · 31 May 2026