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Agent Communication

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codeaholicguy
agent-communication

AI DevKit · Exchange information with active Codex, Claude Code, and other AI agents using ai-devkit agent list, detail, and send. Use when an agent needs to find another active agent, read its recent context, send it information, or request information back.

Overview

Publishercodeaholicguy
Repositoryai-devkit
Skill nameagent-communication
Stars
1.6K
Forks
252
Bundled files
1
LicenseApache-2.0
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.

  • 1 bundled files

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

  • Open source

    Published by codeaholicguy on GitHub. Read the source before you install it.

Installation

Install the Agent Communication 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.
  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/codeaholicguy/ai-devkit.git /tmp/ai-devkit
mkdir -p .claude/skills
cp -r /tmp/ai-devkit/skills/agent-communication .claude/skills/agent-communication
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Communication 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 Communication 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 Communication 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 Communication

Use ai-devkit agent ... to discover and communicate with active agents. If ai-devkit is not on PATH, use npx ai-devkit@latest agent ....

Commands

bash
ai-devkit agent list --json
ai-devkit agent detail --id <agent-name> --json --tail 20
ai-devkit agent send --id <agent-name> "<message>"
ai-devkit agent send --id <agent-name> --wait --timeout 120000 --json "<message>"
<command> 2>&1 | ai-devkit agent send --id <agent-name> --stdin

Notes

  • list --json returns active agents with fields such as name, type, status, summary, projectPath, and lastActive.
  • Use the name from list --json as --id. Partial matches are supported, but exact names are safer.
  • Use detail --json --tail <n> to read recent context from an agent before deciding what to send.
  • send --wait waits for a reply; add --json when the response should be machine-readable.
  • send --stdin forwards piped command output or larger text.

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 Communication AI skill do?

AI DevKit · Exchange information with active Codex, Claude Code, and other AI agents using ai-devkit agent list, detail, and send. Use when an agent needs to find another active agent, read its recent context, send it information, or request information back.

Why use Agent Communication on TypingMind?

Because you install it once and use it with any model. Agent Communication 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 Communication in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/codeaholicguy/ai-devkit/tree/main/skills/agent-communication. 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 Communication?

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 Communication?

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

Is the Agent Communication AI skill free?

Yes. It is published on GitHub by codeaholicguy under the Apache-2.0 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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