Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add NEU-ZHA/legal-ai-skills --skill pkulaw-mcp-labor-employment-answergit clone --depth 1 https://github.com/NEU-ZHA/legal-ai-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/neu-zha/legal-ai-skills/pkulaw-mcp-labor-employment-answer)<a href="https://agentmods.dev/skills/neu-zha/legal-ai-skills/pkulaw-mcp-labor-employment-answer"><img src="https://agentmods.dev/badge/skills/neu-zha/legal-ai-skills/pkulaw-mcp-labor-employment-answer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/neu-zha/legal-ai-skills/pkulaw-mcp-labor-employment-answer"><img src="https://agentmods.dev/badge/skills/neu-zha/legal-ai-skills/pkulaw-mcp-labor-employment-answer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00160 | $0.01286 |
| Opus 5 | $0.00080 | $0.00643 |
| Sonnet 5 | $0.00032 | $0.00257 |
| Haiku 4.5 | $0.00016 | $0.00129 |
Grade A, and why
pkulaw-mcp-labor-employment-answer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
北大法宝 MCP:Labor Employment Answer(劳动用工回复草稿)
这个 Skill 是劳动用工垂直交付层。
如果问题明显是招聘、试用期、调岗、绩效、解除、竞业限制、工时休假、社保等劳动用工问题,优先使用本 Skill,而不是回到通用 pkulaw-mcp-grounded-answer。
这个 Skill 真正要完成的动作
把劳动用工问题压缩成一份可直接发给业务、管理层、HR 或客户初看的答复草稿,通常包括:
- 当前适用前提
- 简短结论
- 主要依据
- 风险提示
- 待复核点
主对象与辅助对象
主对象
- 用户提出的劳动用工问题
- 当前已知事实前提
- 当次检索到的法规、司法解释、典型类案
辅助对象
- 业务同事拟好的回复草稿
- 客户过往沟通口径
- 内部制度摘要
辅助对象只用于理解场景,不当然等于外部法律依据。
缺信息先追问
以下信息缺失时,先补 1-2 个最关键问题:
- 用工地区
- 问题类型:招聘、试用期、调岗、绩效、解除、竞业限制、加班、社保等
- 关键事实前提:是否有书面制度、是否已通知、是否有证据留痕
- 交付对象:内部业务、管理层、客户、HR
- 是否需要类案支撑
如用户暂时无法补齐,只能按“有限事实前提下的初步答复草稿”输出。
推荐工作流
- 界定问题:确认这是劳动用工答复草稿,而不是诉讼策略分析。
- 补足前提:先问地区、事实、制度基础、交付对象。
- 规则检索:优先检索劳动合同法、工时休假、社保、竞业限制等规则依据。
- 类案补充:需要裁判倾向或风险对比时,再补案例检索。
- 草稿成形:先写“结论 + 前提 + 依据 + 风险提示”。
- 引用核验:出现具体法条或司法解释时,用
citation-validator核验。 - 链接增强:需要转发时,再用
doc-link做增强。
输出纪律
- 不写“公司一定可以解除”“员工一定胜诉”等绝对化措辞。
- 事实前提不足时,把“仍需补充的信息”单列出来。
- 若地区差异、裁判分歧明显,要单独提醒。
- 面向业务或 HR 时,优先输出“简要结论 + 主要依据 + 风险提示 + 待复核点”。
质量门槛
- 每个关键结论至少对应一条当次检索依据。
- 重要引用经过
citation-validator,或明确写明未核验。 - 事实不足处已单列,不与结论混写。
- 需要转发时,优先提供
doc-link增强版本。
失败与降级
- 检索为空:明确写“未检索到足够依据”,并提示换关键词、补地区或补事实。
citation-validator不可用:只能标注“引用未核验”,不得写“已确认”。- 类案不足:只能写“当前样本有限,不能据此概括稳定裁判倾向”。
- 若问题明显已超出劳动用工回复范围,应提示转入更深层专项分析,而不是硬写。
配套文件
- 输出模板:template.md
- 真实业务示例:examples.md
关联 Skill
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 106 lines · 160 tokens per session scan A c494ce333954
pkulaw-mcp-labor-employment-answer is a skill published in the GitHub repository NEU-ZHA/legal-ai-skills (64 stars, last pushed 23d ago), licensed MIT. It adds 160 tokens to every session and 1,286 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
specification-writing
A workflow for writing complete patent specifications from patent claims and an invention disclosure. It adapts the document to a chosen jurisdiction, such as the US, Europe, or China.
regulatory-research-fallback
Fallback workflow for regulatory research when web extraction tools fail on government PDFs.
x-scorecard
OpenSSF Scorecard for assessing open source project security. Check security best practices and compliance. Dependency: This is an x-cmd module. Install x-cmd first (see x-cmd skill for installation options). see x-cmd skill for installation.
gesellschaftsrechtliche-satzungen-agb
Für Gesellschaftsrechtliche Satzungen AGB Abgrenzung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: gesellschaftsrechtliche-satzungen-agb.
memstack-business-gdpr
Use this skill when the user says 'GDPR', 'data protection', 'privacy compliance', 'DPA', 'DSAR', 'data subject request', 'cookie consent', 'privacy audit', 'CCPA', or asks 'do I need GDPR for this repo'. Scans the repository to detect what personal data is collected, classifies sensitivity, determines whether GDPR…
nda-review
Use when the user uploads or pastes a non-disclosure agreement and asks for review, redline, risk assessment, or a recommendation on whether to sign. Identifies missing standard protections, one-sided or unusual provisions, and operational issues; produces a structured report with severity ratings and citations to…