agent-mail-automation

agent-mail-automation is a skill for Claude Code, Codex from nevergoodstudy-hub/wechat-article-summarizer. It costs 27 tokens per session (730 once invoked), scanned A, a copy of ably-automation, MIT.

An integration for automating tasks in Agent Mail through the Rube MCP connection. It finds the currently available Agent Mail actions before running them.

In plain words
What is it for?
It helps run Agent Mail workflows from the agent after connecting Agent Mail and confirming that the required tools are active.
Why use it?
It removes the need to move between the coding agent and Agent Mail or guess which actions and inputs are supported.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps run Agent Mail workflows from the agent after connecting Agent Mail and confirming that the required tools are active.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nevergoodstudy-hub/wechat-article-summarizer/agent-mail-automation
Install

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.

Any agent
npx skills add nevergoodstudy-hub/wechat-article-summarizer --skill agent-mail-automation
Clone the repo
git clone --depth 1 https://github.com/nevergoodstudy-hub/wechat-article-summarizer

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for agent-mail-automation

README.md
[![agentmods](https://agentmods.dev/badge/skills/nevergoodstudy-hub/wechat-article-summarizer/agent-mail-automation/github.svg)](https://agentmods.dev/skills/nevergoodstudy-hub/wechat-article-summarizer/agent-mail-automation)
Your own site
<a href="https://agentmods.dev/skills/nevergoodstudy-hub/wechat-article-summarizer/agent-mail-automation"><img src="https://agentmods.dev/badge/skills/nevergoodstudy-hub/wechat-article-summarizer/agent-mail-automation/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.

agentmods 80×15 button for agent-mail-automation

Your own site · 80×15
<a href="https://agentmods.dev/skills/nevergoodstudy-hub/wechat-article-summarizer/agent-mail-automation"><img src="https://agentmods.dev/badge/skills/nevergoodstudy-hub/wechat-article-summarizer/agent-mail-automation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 730 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 81% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00027 $0.00730
Opus 5 $0.00014 $0.00365
Sonnet 5 $0.00005 $0.00146
Haiku 4.5 $0.00003 $0.00073

Measured 9d ago against content hash 72bdf3b3772f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

agent-mail-automation 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 9d 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.

Origin

This is a copy

81% identical to ably-automation — 24 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.

.warp/skills/agent-mail-automation/SKILL.md · 92 lines

How it starts

The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Mail Automation via Rube MCP

Automate Agent Mail operations through Composio's Agent Mail toolkit via Rube MCP.

Toolkit docs: composio.dev/toolkits/agent_mail

Prerequisites

  • Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
  • Active Agent Mail connection via RUBE_MANAGE_CONNECTIONS with toolkit agent_mail
  • Always call RUBE_SEARCH_TOOLS first to get current tool schemas

Setup

Get Rube MCP: Add https://rube.app/mcp as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.

  1. Verify Rube MCP is available by confirming RUBE_SEARCH_TOOLS responds
  2. Call RUBE_MANAGE_CONNECTIONS with toolkit agent_mail
  3. If connection is not ACTIVE, follow the returned auth link to complete setup
  4. Confirm connection status shows ACTIVE before running any workflows

Tool Discovery

Always discover available tools before executing workflows:

RUBE_SEARCH_TOOLS
queries: [{use_case: "Agent Mail operations", known_fields: ""}]
session: {generate_id: true}

This returns available tool slugs, input schemas, recommended execution plans, and known pitfalls.

Core Workflow Pattern

Step 1: Discover Available Tools

RUBE_SEARCH_TOOLS
queries: [{use_case: "your specific Agent Mail task"}]
session: {id: "existing_session_id"}

Step 2: Check Connection

RUBE_MANAGE_CONNECTIONS
toolkits: ["agent_mail"]
session_id: "your_session_id"

Step 3: Execute Tools

RUBE_MULTI_EXECUTE_TOOL
tools: [{
  tool_slug: "TOOL_SLUG_FROM_SEARCH",
  arguments: {/* schema-compliant args from search results */}
}]
memory: {}
session_id: "your_session_id"

Known Pitfalls

  • Always search first: Tool schemas change. Never hardcode tool slugs or arguments without calling RUBE_SEARCH_TOOLS
  • Check connection: Verify RUBE_MANAGE_CONNECTIONS shows ACTIVE status before executing tools
  • Schema compliance: Use exact field names and types from the search results
  • Memory parameter: Always include memory in RUBE_MULTI_EXECUTE_TOOL calls, even if empty ({})
  • Session reuse: Reuse session IDs within a workflow. Generate new ones for new workflows
  • Pagination: Check responses for pagination tokens and continue fetching until complete

Read the full file on GitHub · 92 lines

Changes

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.

  1. 9d ago First seen · 92 lines · 27 tokens per session scan A 72bdf3b3772f

Subscribe to this mod's changes

agent-mail-automation is a skill published in the GitHub repository nevergoodstudy-hub/wechat-article-summarizer (5 stars, last pushed 2mo ago), licensed MIT. It adds 27 tokens to every session and 730 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to ably-automation, differing in 24 lines, and is treated as a copy.

Related

Other skills, from other repositories

knowledge-base-management

A lifecycle system for managing an Obsidian knowledge base, which is a folder of linked notes. It organizes raw material, AI-maintained wiki pages, and generated views into separate layers.

chubbyguan/chubbyskills · 49 tokens

daily-update

Run the daily wiki maintenance cycle: check all source freshness, update the index, and regenerate hot.md. Use this skill when the user says "/daily-update", "run the daily update", "update everything", "morning sync", "refresh the wiki index", or when triggered by the launchd cron at 9 AM. Also use to set up or…

Ar9av/obsidian-wiki · 109 tokens

setup-brain

Set up or upgrade an AI-powered Obsidian vault. Interviews you, builds your vault structure (or works with what you already have), creates your CLAUDE.md memory file, installs tools, and gets you journaling — all in one conversation. Also has a repair/upgrade path for existing users.

mycelium-hq/ai-brain-starter · 66 tokens

coach

Use when the user says /coach (today, week, month, profile, log), asks what to do today for training, asks for a workout, weekly training plan, or longevity plan, wants to log a finished workout or check lift progression (PR, plateau, deload), or a scheduled morning task fires to drop today's workout into the…

mycelium-hq/ai-brain-starter · 103 tokens

patterns

Use when the user says /patterns or mentions the Instinct Engine, says "I keep noticing" or "this keeps coming up", after a weekly review, when a pattern is hardening, or at session end after repeated corrections, 5+ tool-call friction on a routine task, dead-end backtracking, or an undocumented discovery. Also as a…

mycelium-hq/ai-brain-starter · 104 tokens

for-my-team

Use when a user wants the team or company version of ai-brain-starter — any variant of 'how do I add my team to this,' 'can my team use this,' 'optimize this for my company,' 'what does the team version look like,' 'install this for my whole company,' 'how does this work with multiple people,' or worries about mixing…

mycelium-hq/ai-brain-starter · 95 tokens