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 email-formal-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/email-formal-zh)<a href="https://agentmods.dev/skills/agiwish/hermes-skills-zh/email-formal-zh"><img src="https://agentmods.dev/badge/skills/agiwish/hermes-skills-zh/email-formal-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/email-formal-zh"><img src="https://agentmods.dev/badge/skills/agiwish/hermes-skills-zh/email-formal-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 | $0.00052 | $0.00641 |
| Opus 5 | $0.00026 | $0.00320 |
| Sonnet 5 | $0.00010 | $0.00128 |
| Haiku 4.5 | $0.00005 | $0.00064 |
Grade A, and why
email-formal-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
商务邮件 (email-formal-zh)
When to Use
- "帮我写一封邮件"、"起草一封商务邮件"
- 用户描述了邮件场景（催进度/道歉/提案/感谢等）
/email-formal-zh [场景描述]
Quick Reference
/email-formal-zh [场景描述]
常用场景关键词：
跟进 | 催促 | 道歉 | 提案 | 感谢 | 确认 | 拒绝 | 投诉
Procedure
-
识别场景类型和要素
- 发件人身份 / 收件人身份
- 邮件目的（一句话说清楚）
- 核心诉求或信息
- 期望对方的行动（如有）
-
生成邮件
主题：[简洁明确，15字以内] [收件人称呼]，您好！ [开场句：说明写信目的，1句话] [正文：2-3段，每段聚焦一个要点] - 段1：背景/现状 - 段2：核心诉求/信息 - 段3：期望对方行动/截止时间（如有） [结尾礼貌用语] 如有任何问题，欢迎随时与我联系。 此致 敬礼 [签名] [日期] -
场景特殊处理
- 道歉邮件：先道歉，再解释，再给出解决方案，不要过度辩解
- 催促邮件：语气礼貌但明确，给出截止时间
- 拒绝邮件：先感谢，再委婉说明无法接受，提供替代方案
Pitfalls
- 主题行要具体，避免「关于合作的邮件」这类模糊标题
- 正文不超过 300 字，商务邮件要简洁
- 不要在邮件中写「如您所知」（暗示对方应该知道）
Verification
- 主题行是否清晰具体
- 是否明确了期望对方的行动
- 语气是否与场景匹配（道歉/催促/感谢各有分寸）
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 · 78 lines · 52 tokens per session scan A bd11668c64f6
email-formal-zh is a skill published in the GitHub repository AgiWish/hermes-skills-zh (5 stars, last pushed 3mo ago), licensed MIT. It adds 52 tokens to every session and 641 once invoked, about $0.0003 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.
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