agentmail
Inter-agent communication for tmux sessions. Send and receive messages between AI agents.
What this skill does
# AgentMail Skill AgentMail enables communication between AI agents running in different tmux windows through a simple file-based mail system. ## Overview AgentMail is a CLI tool for inter-agent communication within tmux sessions. Messages are stored in `.agentmail/mailboxes/` as JSONL files, providing persistent, file-locked message queues for each agent. ## Prerequisites - Must be running inside a tmux session - AgentMail CLI must be installed and available in PATH - Messages stored in `.agentmail/` directory ## Core Commands ### Send a Message ```bash agentmail send <recipient> "<message>" ``` Send a message to another agent. The recipient must be a valid tmux window name. **Examples:** ```bash agentmail send agent2 "Can you review the changes in src/api?" agentmail send -r worker -m "Task completed" echo "Build succeeded" | agentmail send agent2 ``` ### Receive Messages ```bash agentmail receive ``` Read the oldest unread message from your mailbox. Messages are delivered in FIFO order and marked as read after display. ### List Recipients ```bash agentmail recipients ``` List all tmux windows that can receive messages. Your current window is marked with `[you]`. ### Set Status ```bash agentmail status <ready|work|offline> ``` Set your availability status: - `ready` - Available to receive messages and notifications - `work` - Busy working (suppresses notifications) - `offline` - Not available (suppresses notifications) ## Workflow ### Checking for Messages 1. Run `agentmail receive` to check for new messages 2. If a message is available, read and process it 3. Optionally reply using `agentmail send` ### Sending Messages 1. Run `agentmail recipients` to see available agents 2. Send your message: `agentmail send <recipient> "<message>"` 3. Confirm delivery via the returned message ID ### Status Management The plugin automatically manages your status: - **Session start**: Status set to `ready` - **Session end**: Status set to `offline` - **End of turn (Stop)**: Status set to `ready`, checks for new messages ## Message Format Messages include: - **ID**: Unique 8-character base62 identifier (a-z, A-Z, 0-9) - **From**: Sender's tmux window name - **To**: Recipient's tmux window name - **Content**: Message body ## Best Practices 1. **Check messages regularly** - Use `agentmail receive` to stay informed 2. **Keep messages concise** - Focus on actionable information 3. **Include context** - Reference files, line numbers, or specific details 4. **Respond promptly** - Other agents may be waiting for your input 5. **Use status appropriately** - Set `work` when focusing on complex tasks ## Integration with Claude Code This plugin integrates with Claude Code hooks: - **SessionStart**: Automatically sets status to `ready` and runs onboarding - **SessionEnd**: Automatically sets status to `offline` - **Stop**: Sets status to `ready` and checks for new messages The hooks ensure agents are properly registered and can receive notifications from the mailman daemon. ## Troubleshooting ### "Not in a tmux session" AgentMail requires tmux. Start a tmux session first. ### "Recipient not found" The recipient window doesn't exist. Check available windows with `agentmail recipients`. ### "No unread messages" Your mailbox is empty. Other agents haven't sent you messages yet. ### Messages not being delivered Ensure the mailman daemon is running: `agentmail mailman --daemon`
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.