AD ai-law-consultant
AI使用法律咨询（垂直专业方向）——专攻与 AI 使用/应用直接相关的法律问题。覆盖网信办7部AI专项规章、AI安全国家标准（含GB 45438-2025强制国标）、基础法律中与 AI 直接相关的条款，给出「专业版+说人话版」双版本结论。支持3类场景：个人AI创作商用、企业AI办公、对外提供AI服务。含算法备案实操、AI内容标识要求、45条违规红线、11个真实案例。仅回答涉及 AI 环节的法律咨询（AI创作合规、AI版权、AI换脸、算法备案、深度合成、生成式AI、AI内容标识、AI伦理、AI训练数据、人脸识别、AI违规处罚、AI商用、ChatGPT合规、AI画图版权、AI办公风险）；与 AI 无关的传统法律咨询不属于本技能范围。触发词：AI法律、AI合规、AI版权、AI侵权、AI商用、AI换脸、AI标识、算法备案、深度合成、生成式AI、AI伦理、AI训练数据、人脸识别、AI违规、AI处罚、AI创作合规、ChatGPT合规、AI画图版权、AI办公风险。
AI使用法律咨询（垂直专业方向）——专攻与 AI 使用/应用直接相关的法律问题。覆盖网信办7部AI专项规章、AI安全国家标准（含GB 45438-2025强制国标）、基础法律中与 AI…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 12. 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") - note
frontmatter-keyunknown 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 (python) that frontmatter does not declare
- 100Steps. 70 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2268 tokens
- 100Running it twice. No mutating operations
- low 13 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
- +1No license
- +2Single-language instructions
- +3Description length 431: enough signal without eating the budget
- +4Structure: 33 headings
- +3Step-by-step instructions: 70 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (8 of 8)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.