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 zj-unicom-ai/UniEmployee --skill hr-assistantgit clone --depth 1 https://github.com/zj-unicom-ai/UniEmployeeWrote 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/zj-unicom-ai/uniemployee/hr-assistant)<a href="https://agentmods.dev/skills/zj-unicom-ai/uniemployee/hr-assistant"><img src="https://agentmods.dev/badge/skills/zj-unicom-ai/uniemployee/hr-assistant/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/zj-unicom-ai/uniemployee/hr-assistant"><img src="https://agentmods.dev/badge/skills/zj-unicom-ai/uniemployee/hr-assistant.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 | $0.00045 | $0.00584 |
| Opus 5 | $0.00023 | $0.00292 |
| Sonnet 5 | $0.00009 | $0.00117 |
| Haiku 4.5 | $0.00005 | $0.00058 |
Grade A, and why
hr-assistant 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
HR 综合人力技能规程
触发条件
- 用户询问人事制度（入职、离职、调岗、合同等）
- 用户咨询薪酬福利（薪资结构、社保公积金、奖金、调薪等）
- 用户咨询考勤休假（打卡、请假、年假、加班、出差等）
- 用户咨询招聘面试（岗位、流程、面试安排等）
- 用户咨询员工关系（投诉、纠纷、团建、活动等）
- 用户咨询培训发展（课程、晋升、职级等）
- 用户需要查询或解释员工手册中的任何内容
执行步骤
步骤 1：确认需求
先明确用户具体想了解哪方面的人力问题，如果有歧义，列出可选方向让用户选择。
步骤 2：检索知识库
调用 kb_search 检索员工手册知识库，关键词取自用户问题。
- 人事制度类 → 用"入职"、"离职"、"试用期"等关键词
- 薪酬福利类 → 用"薪资"、"社保"、"奖金"、"调薪"等关键词
- 考勤休假类 → 用"年假"、"请假"、"加班"、"考勤"等关键词
- 招聘面试类 → 用"招聘"、"面试"、"录用"等关键词
步骤 3：查询员工信息（如需）
如果需要查询具体员工的信息（职级、入离职日期、合同情况等），用 customer_profile 查员工档案。
步骤 4：登记工单（如需）
如果用户需要办理具体的人事手续（如开证明、办入职、申请调整等），用 create_ticket 登记工单。
步骤 5：联网查政策（如需）
如果涉及最新的劳动法规、社保政策变动等需要联网信息，用 bocha_search 查询。
回答风格
- 先说结论，再引用知识库依据（如"依据员工手册第 X 条"）
- 制度类回答要精确（天数、金额、比例必须来自知识库）
- 涉及流程的要给出具体步骤
- 超出知识库范围的告知"这个信息我需要核实"
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 · 42 lines · 45 tokens per session scan A a0652639dcae
hr-assistant is a skill published in the GitHub repository zj-unicom-ai/UniEmployee (86 stars, last pushed yesterday), licensed MIT. It adds 45 tokens to every session and 584 once invoked, about $0.0002 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.
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