Agent Message logo

Agent Message

Organization
7df-lab
agent-message

Message an agent's parent, siblings, or direct children through the daemon. Discover reachable agents with agent_observe.list_agents, then send direct text without spoofing sender identity.

Overview

Publisher7df-lab
Repositorydevo
Skill nameagent-message
Stars
341
Forks
139
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by 7df-lab on GitHub. Read the source before you install it.

Installation

Install the Agent Message AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/7df-lab/devo/tree/main/crates/skills/assets/bundled/agent-message
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/7df-lab/devo.git /tmp/devo
mkdir -p .claude/skills
cp -r /tmp/devo/crates/skills/assets/bundled/agent-message .claude/skills/agent-message
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Message in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Message on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Message is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agent Message

Send direct messages within the current agent's nuclear family through the local daemon: parent, siblings, and direct children only. Roots are siblings of each other only when they share a parent worker; a root has no parent to message. The daemon derives your sender identity from the current session; do not try to include a from field.

Call directly from the kernel:

python
roster = await agent_observe.list_agents()
child = next(
    (
        item
        for item in roster.get("agents", [])
        if item.get("relationship") == "child"
    ),
    None,
)
if child is not None:
    receipt = await agent_message.send(
        "Please inspect the latest result.",
        receiver_role="child",
        receiver_name=child.get("sessionName") or child["sessionId"],
    )

API

  • await agent_observe.list_agents() (agent-observe skill) is the roster: it lists the parent, siblings, and children this skill can reach, active or not, with the relationship and sessionName that send takes as receiver_role and receiver_name.
  • await agent_message.send(message, receiver_role="parent" | "sibling" | "child", receiver_name=None) — sends one direct text message to one family member. Sending to an inactive or idle completed subagent wakes it and starts an ordinary follow-up turn in that same session and context. The child remains available only until its parent session closes. The daemon resolves receiver_role within the current agent family; receiver_name is required for siblings and children and omitted for the unique parent. send("all", message) broadcasts only to the family roster and returns {receipts: [...]} in roster order; successful entries are ordinary receipts and failed entries contain the target id and a short error. One failed delivery does not reject successful deliveries. Messages always use steering delivery so a busy target sees them during its active run. Returns a receipt with a deliveryStatus field: "delivered" means the message reached an idle target's context; "queued" means a steering message was accepted and will deliver when the target's current work allows (send does not block waiting for that). Delivered receipts carry deliveredAt, queued receipts carry queuedAt.

Safety

  • Do not delete a child immediately after send: delivered follow-ups may still be running and queued receipts have not run yet. Wait until observation shows the child is idle and its context is no longer needed before closing it.
  • Reach is limited to parent, siblings, and direct children; relay through an intermediate child instead of messaging grandchildren or cousins directly.
  • Sender identity is daemon-derived and cannot be spoofed from Python.
  • The daemon enforces message size, rate, and pending-queue limits before accepting delivery.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Agent Message AI skill do?

Message an agent's parent, siblings, or direct children through the daemon. Discover reachable agents with agent_observe.list_agents, then send direct text without spoofing sender identity.

Why use Agent Message on TypingMind?

Because you install it once and use it with any model. Agent Message is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Message in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/7df-lab/devo/tree/main/crates/skills/assets/bundled/agent-message. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Agent Message?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Message?

As many as you like. As long as a model supports skills, you can use Agent Message with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Message AI skill free?

Yes. It is published on GitHub by 7df-lab under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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