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 lingxling/awesome-skills-cn --skill agentmailgit clone --depth 1 https://github.com/lingxling/awesome-skills-cnWrote 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/lingxling/awesome-skills-cn/agentmail)<a href="https://agentmods.dev/skills/lingxling/awesome-skills-cn/agentmail"><img src="https://agentmods.dev/badge/skills/lingxling/awesome-skills-cn/agentmail/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/lingxling/awesome-skills-cn/agentmail"><img src="https://agentmods.dev/badge/skills/lingxling/awesome-skills-cn/agentmail.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 | $0.00031 | $0.02271 |
| Opus 5.5 | $0.00012 | $0.00908 |
| Sonnet 5.5 | $0.00006 | $0.00454 |
| Haiku 4.5 | $0.00003 | $0.00227 |
Grade A, and why
agentmail scanned grade A with 1 finding 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 19d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST https://api.theagentmail.net/v1/accounts \ This is a copy
98% identical to agentmail — 93 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentMail — Email for AI Agents
AgentMail gives AI agents real email addresses (@theagentmail.net) with a REST API. Agents can send and receive email, sign up for services (GitHub, AWS, Slack, etc.), and get verification codes. A karma system prevents spam and keeps the shared domain's reputation high.
Base URL: https://api.theagentmail.net
When to Use
- An AI agent needs a real inbox/outbox for signups, verification flows, or transactional communication.
- You need to provision AgentMail accounts, send messages, read inbox contents, or register inbound webhooks.
- You need to monitor karma usage or wire email events into agent automation.
Quick start
All requests require Authorization: Bearer am_... header (API key from dashboard).
Create an email account (-10 karma)
curl -X POST https://api.theagentmail.net/v1/accounts \
-H "Authorization: Bearer am_..." \
-H "Content-Type: application/json" \
-d '{"address": "[email protected]"}'
Response: {"data": {"id": "...", "address": "[email protected]", "displayName": null, "createdAt": 123}}
Send email (-1 karma)
curl -X POST https://api.theagentmail.net/v1/accounts/{accountId}/messages \
-H "Authorization: Bearer am_..." \
-H "Content-Type: application/json" \
-d '{
"to": ["[email protected]"],
"subject": "Hello from my agent",
"text": "Plain text body",
"html": "<p>Optional HTML body</p>"
}'
Optional fields: cc, bcc (string arrays), inReplyTo, references (strings for threading), attachments (array of {filename, contentType, content} where content is base64).
Read inbox
# List messages
curl https://api.theagentmail.net/v1/accounts/{accountId}/messages \
-H "Authorization: Bearer am_..."
# Get full message (with body and attachments)
curl https://api.theagentmail.net/v1/accounts/{accountId}/messages/{messageId} \
-H "Authorization: Bearer am_..."
Check karma
curl https://api.theagentmail.net/v1/karma \
-H "Authorization: Bearer am_..."
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.
- 19d ago First seen · 259 lines · 31 tokens per session scan A 4bb4a388fa29
agentmail is a skill published in the GitHub repository lingxling/awesome-skills-cn (321 stars, last pushed 19d ago), licensed MIT. It adds 31 tokens to every session and 2,271 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 98% identical to agentmail, differing in 93 lines, and is treated as a copy.
Other skills, from other repositories
simp
A relationship-advice skill that helps interpret signals, plan respectful approaches, and write sincere messages for someone you like.
mm-init-project
A project setup workflow that creates a shared project record in Markdown files, including a passport, dashboard, handoff notes, and instructions for Claude.ai. Obsidian is a note-taking app that can store these files as a connected project vault.
mm
A dispatcher that provides short /mm commands for project setup, session recovery, project overviews, and workflow checks. It maps these aliases to longer system commands.
mm-projects
A read-only overview of all registered projects stored in Obsidian notes. It shows each project's status, type, current GSD phase, recent activity, and number of open questions.
resemble-detect
Deepfake detection and media safety — detect AI-generated audio, images, video, and text, trace synthesis sources, apply watermarks, verify speaker identity, and analyze media intelligence using Resemble AI.
algorithmic-art
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright…