Agent Observe logo

Agent Observe

Organization
7df-lab
agent-observe

Read-only roster and observation of an agent's parent, siblings, and direct children. Use to discover reachable agents and to inspect family status and bounded recent-message previews without mutating sessions.

Overview

Publisher7df-lab
Repositorydevo
Skill nameagent-observe
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 Observe 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-observe
  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-observe .claude/skills/agent-observe
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Observe 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 Observe 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 Observe 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 Observe

Observe the current agent's nuclear family through the local daemon: parent, siblings, direct children, and self. list_agents is the one family roster and covers every member agent_message.send can reach. get_agent and recent_messages hydrate an inactive child before reading it. They cannot read a root sibling that has no live session in this worker. This skill is read-only: it can list family sessions, inspect one session, and fetch bounded recent message previews. It cannot prompt, steer, clear, kill, rename, or otherwise mutate another session.

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:
    name = child.get("sessionName") or child["sessionId"]
    worker = await agent_observe.get_agent(name)
    recent = await agent_observe.recent_messages(name, limit=6)

API

  • await agent_observe.list_agents() returns current and agents, the full nuclear family: parent, siblings, and direct children, active or not. Each agent carries sessionId, optional sessionName, relationship (parent/sibling/child/self), status, isSessionActive, and the counts and message previews known for it: latestMessage for a live session, firstMessage for an inactive child. A member with no live session has no activeSessionId and no live detail; address it with agent_message.send using its relationship plus its sessionName, or its sessionId when the member has no name.
  • await agent_observe.get_agent(target) returns agent, where agent contains one live agent summary. target is resolved like other live-session selectors: active id, session id/name, or unambiguous suffix.
  • await agent_observe.recent_messages(target, limit=8, max_chars=800) returns up to limit recent bounded message previews for the target session. limit must be 1-50, and max_chars must be 80-2000.

Safety

  • This skill is read-only and exposes no mutation commands.
  • Targets outside the nuclear family are rejected; transcript reads follow the same family rule as messaging.
  • Message access is bounded by count and per-message character limit.
  • Prefer status and recent previews for orchestration. Ask the user before using observed context to steer or message another session.

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 Observe AI skill do?

Read-only roster and observation of an agent's parent, siblings, and direct children. Use to discover reachable agents and to inspect family status and bounded recent-message previews without mutating sessions.

Why use Agent Observe on TypingMind?

Because you install it once and use it with any model. Agent Observe 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 Observe 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-observe. 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 Observe?

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 Observe?

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

Is the Agent Observe 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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