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 AgiWish/hermes-skills-zh --skill leave-request-zhgit clone --depth 1 https://github.com/AgiWish/hermes-skills-zhWrote 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/agiwish/hermes-skills-zh/leave-request-zh)<a href="https://agentmods.dev/skills/agiwish/hermes-skills-zh/leave-request-zh"><img src="https://agentmods.dev/badge/skills/agiwish/hermes-skills-zh/leave-request-zh/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/agiwish/hermes-skills-zh/leave-request-zh"><img src="https://agentmods.dev/badge/skills/agiwish/hermes-skills-zh/leave-request-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00042 | $0.00536 |
| Opus 5 | $0.00021 | $0.00268 |
| Sonnet 5 | $0.00008 | $0.00107 |
| Haiku 4.5 | $0.00004 | $0.00054 |
Grade A, and why
leave-request-zh 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
请假申请 (leave-request-zh)
When to Use
- "帮我写请假申请"、"我要请假,帮我说一下"
- 用户描述了请假原因和时间
/leave-request-zh [请假原因和时间]
Quick Reference
/leave-request-zh [请假原因] [时间]
可选:
--style=正式 # 正式书面申请(默认)
--style=微信 # 微信/钉钉消息版
--type=事假|病假|年假|调休
Procedure
-
提取关键信息
- 请假类型(事假/病假/年假/调休)
- 请假时间(开始日 ~ 结束日,共X天)
- 原因(如用户不想透露,用「个人事务」代替)
- 工作交接(如有提及)
-
正式版生成
[姓名/此处留空] 请假申请 申请人:[留空] 请假类型:[类型] 请假时间:[开始] 至 [结束],共 [X] 天 请假原因:[原因] 工作安排: [如用户提供了交接信息,填写;否则填「请假期间如有紧急事务,可通过电话联系」] 恳请批准,谢谢! -
微信版生成
[上级称呼],我[时间]需要请[类型] [X] 天,[一句话原因]。工作已[交接安排/会保持手机畅通],请审批,谢谢!
Pitfalls
- 病假不要求用户写太详细的病情
- 如时间跨度超过3天,提示用户可能需要补充工作交接说明
Verification
- 包含请假类型、时间、天数
- 有工作安排说明
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 · 69 lines · 42 tokens per session scan A 73d8e98a185f
leave-request-zh is a skill published in the GitHub repository AgiWish/hermes-skills-zh (5 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 536 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 2026-08-31.
Other skills, from other repositories
hermespace
Full Hermespace pocket workbench for Hermes Agent (v0.18+): concept, dual decode, workbench I/O, fabric skills+MEMORY, FOA desk, Pulse, viewport app-shell, Tailscale serve, pocket boundary, autonomy grid, Desktop plugin, ops boot/doctor/smoke. Use for hermespace, pocket, workbench, FOA, pulse, viewport, access…
21-day-self-interview
A 21-night guided self-reflection routine in which an agent asks three questions each night, remembers the answers, and reflects on them at key points.
awesome-literature-review
A Chinese-language workflow for writing narrative academic literature reviews, which summarize and assess existing research on a topic.
persona-compass
Build personality models of colleagues, clients, friends, or family members and get AI-powered communication strategies. Use this skill whenever the user wants to: understand someone's personality, predict how someone will react, get advice on communicating with a difficult person, prepare for a tough conversation…
ai-tips-tricks
An automated workflow for searching the web for practical AI tips, techniques, and workflows, then writing tutorial-style Chinese posts and sending them to Telegram.
pingpong
Spontaneous local leisure meetups via a shared agent board: publish, discover and match offers, then negotiate place & time agent-to-agent. ALWAYS use this skill when the user spontaneously wants to do something or says: "publish an offer", "I want to play table tennis / X", "fancy a ...", "who's free for ...", "find…