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Observal Agents

OrganizationPopular
Observal
observal-agents

Creates, authors, validates, publishes, updates, versions, pulls, archives, restores, transfers, and manages co-authors for Observal Agents. Use when the user wants to build or install an Agent, change an Agent definition, publish a draft, release a version, or manage Agent ownership.

Overview

PublisherObserval
RepositoryObserval
Skill nameobserval-agents
Stars
2.4K
Forks
472
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 Observal on GitHub. Read the source before you install it.

Installation

Install the Observal Agents 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/Observal/Observal.git /tmp/Observal
mkdir -p .claude/skills
cp -r /tmp/Observal/observal_cli/skills/observal-agents .claude/skills/observal-agents
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Observal Agents 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 Observal Agents 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 Observal Agents 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.

Managing Observal Agents

Execution contract

  1. Execute commands with a 60 second timeout.
  2. Use machine output by default: add --output json whenever supported. Parse list results from items and pagination fields.
  3. Use --help before acting when a path or flag is uncertain.
  4. Keep workflows noninteractive. Supply required fields, --no-prompt, and confirmation flags.
  5. Use UUIDs or qualified_name values returned by JSON. Never automate with row numbers.
  6. Prefer native agent init, agent add, and agent build over hand-written scaffolding or custom validation.
  7. Verify every publish, release, pull, ownership, and lifecycle mutation.
  8. Never print MCP environment values, headers, tokens, or other secrets.
  9. Mutations are sent once. After an uncertain transport failure, read Agent state before retrying.

Choose the workflow

User intentWorkflow
Find or inspect an AgentDiscover and inspect
Install an existing Agent into a harnessPull and verify
Create a simple Agent in one callDirect create
Author an Agent with components or filesInit, add, build, publish
Change the current listing without a new reviewed versionUpdate in place
Publish a reviewed patch, minor, or major versionRelease
Create many Agents from a prepared fileBulk create
Archive, restore, transfer, or manage co-authorsLifecycle and collaboration

Read Agent workflows completely before executing the selected workflow.

State rules

  • create without complete flags starts a wizard. Agents must provide all required inputs or use a file.
  • publish --update changes the current Agent in place.
  • release --bump creates a reviewed version. Do not use update when the user asked for a release.
  • Public teamspace publication may remain private with a pending visibility or listing review. Report the actual returned status.
  • Pull success requires checking files, warnings, and setup_commands. Partial setup is not success.
  • A 409 is a decision point, not a generic retry signal. Read current state before choosing update or release.

Completion

Report the canonical Agent identity, resulting status and version, files changed for local operations, warnings, and the smallest next action. Verify with agent show, agent versions, or scan when the mutation response is not sufficient.

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 Observal Agents AI skill do?

Creates, authors, validates, publishes, updates, versions, pulls, archives, restores, transfers, and manages co-authors for Observal Agents. Use when the user wants to build or install an Agent, change an Agent definition, publish a draft, release a version, or manage Agent ownership.

Why use Observal Agents on TypingMind?

Because you install it once and use it with any model. Observal Agents 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 Observal Agents in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Observal/Observal/tree/main/observal_cli/skills/observal-agents. 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 Observal Agents?

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 Observal Agents?

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

Is the Observal Agents AI skill free?

Yes. It is published on GitHub by Observal 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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