Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/xyva-yuangui/XyvaClawnpx agentmods add skills/xyva-yuangui/xyvaclaw/emailWrote 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/xyva-yuangui/xyvaclaw/email)<a href="https://agentmods.dev/skills/xyva-yuangui/xyvaclaw/email"><img src="https://agentmods.dev/badge/skills/xyva-yuangui/xyvaclaw/email/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/xyva-yuangui/xyvaclaw/email"><img src="https://agentmods.dev/badge/skills/xyva-yuangui/xyvaclaw/email.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 | $0.00034 | $0.00623 |
| Opus 5 | $0.00017 | $0.00311 |
| Sonnet 5 | $0.00007 | $0.00125 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
email 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
Email — 邮件收发
通过 IMAP/SMTP 协议收发邮件。
功能
- 读取邮件 — 获取收件箱最新邮件（标题、发件人、正文、附件）
- 搜索邮件 — 按发件人、主题、日期范围搜索
- 发送邮件 — 发送纯文本或 HTML 邮件，支持附件
- 回复邮件 — 回复指定邮件
- 下载附件 — 保存邮件附件到本地
使用方式
# 健康检查
python3 scripts/check.py
# 读取最新 10 封邮件
python3 scripts/email_tool.py inbox --limit 10
# 搜索邮件
python3 scripts/email_tool.py search --from "[email protected]" --days 7
# 读取指定邮件详情
python3 scripts/email_tool.py read --id 12345
# 发送邮件
python3 scripts/email_tool.py send --to "[email protected]" --subject "标题" --body "内容"
# 发送带附件的邮件
python3 scripts/email_tool.py send --to "[email protected]" --subject "报告" --body "见附件" --attach report.pdf
# 下载附件
python3 scripts/email_tool.py download-attachments --id 12345 --output-dir ./attachments/
配置
在 $OPENCLAW_HOME/.env 中添加：
EMAIL_IMAP_HOST=imap.gmail.com
EMAIL_IMAP_PORT=993
EMAIL_SMTP_HOST=smtp.gmail.com
EMAIL_SMTP_PORT=587
[email protected]
EMAIL_PASSWORD=your-app-password
[email protected]
常见邮箱配置：
- Gmail: IMAP imap.gmail.com:993, SMTP smtp.gmail.com:587（需开启应用专用密码）
- QQ邮箱: IMAP imap.qq.com:993, SMTP smtp.qq.com:587（需开启 IMAP 并获取授权码）
- 163邮箱: IMAP imap.163.com:993, SMTP smtp.163.com:465
- Outlook: IMAP outlook.office365.com:993, SMTP smtp.office365.com:587
输出目录
$OPENCLAW_HOME/workspace/output/email/
依赖
Python 标准库（imaplib, smtplib, email），无需额外安装。
What ships with it
2 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 · 77 lines · 34 tokens per session scan A 170140e23f69
email is a skill published in the GitHub repository xyva-yuangui/XyvaClaw (21 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 623 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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