Orchestration

OrganizationPopular

stablyai

orchestration

Coordinate supervised Orca workers: threaded messages, blocking ask/reply, task dispatch, worker_done/escalation waits, task DAGs, decision gates, coordinator loops, and decomposing work across agents. Use `orca-cli` for full ownership handoffs — "hand off", "handoff", "handover", "give this to another agent", "another worktree" — unless asked to supervise, monitor, or coordinate a DAG, and for terminal control, lightweight terminal prompts, shell commands, Orca worktree management, and reading or waiting on terminals.

Overview

Publisher	stablyai
Repository	`orca`
Skill name	`orchestration`
Stars	82.5K
Forks	5.4K
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by stablyai on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/stablyai/orca/tree/main/skills/orchestration
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.

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/stablyai/orca.git /tmp/orca
mkdir -p .claude/skills
cp -r /tmp/orca/skills/orchestration .claude/skills/orchestration

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Orchestration 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 Orchestration 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 Orchestration 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.

Orca Orchestration

This file is a discovery stub, not the usage guide. The full, version-matched Orca orchestration reference is served by the orca binary itself — kept out of this file on purpose so it can never drift from the binary that will actually run your commands.

Engage Orca orchestration whenever you need structured multi-agent coordination: threaded messages, blocking ask/reply flows, task dispatch, worker_done/escalation waits, task DAGs, decision gates, coordinator loops, or decomposing work across agents. Use the orca-cli skill instead for full ownership handoffs ("hand off", "handoff", "handover", "give this to another agent", "another worktree") when the user did not ask to supervise, monitor, wait for results, or coordinate a DAG — and for ordinary terminal control, shell commands, worktree management, and the built-in browser. Coordination requires real Orca runtime state; never substitute a non-Orca subagent tool.

Resolve the CLI for this session

Choose the executable once and reuse it for every later command:

If the ORCA_CLI_COMMAND environment variable is set, use its value. Orca exports this for managed WSL sessions.
Otherwise, in a dev checkout whose session exposes ORCA_DEV_REPO_ROOT, use orca-dev.
Otherwise, on Linux outside an Orca-managed terminal, use orca-ide. Never run bare orca there — outside Orca's terminals it normally resolves to the GNOME Orca screen reader (/usr/bin/orca) and starts speech on the user's machine.
Otherwise, use orca.

Below, ORCA is a placeholder for the executable you resolved. Substitute it before running anything; do not create a shell variable or run ORCA literally. This works the same way in POSIX shells, PowerShell, and cmd.exe.

If the selected executable cannot run, report its exact error and stop. Do not fall through to another executable, which could silently target a different Orca build.

Load the version-matched guide before running Orca commands

text
ORCA skills get orchestration

That prints the compact, version-matched guide for the exact binary that will handle your next commands. It covers the normal local coordinator loop. For a conditional action gate such as remote placement, uncertain release recovery, or expanded DAG work, load only the reference that gate names with ORCA skills get orchestration --reference references/<file>.md (--references lists the names). If that binary rejects --reference, run ORCA skills get orchestration --full and read the named bundled reference before acting.

Prefer --json. Use the selected executable's --help for commands or flags the guide does not cover. If a command reports that Orca is not running, start it with ORCA open --json and retry. If it fails with runtime_access_denied, your sandbox blocked the connection: re-run it with escalated permissions, and do not run ORCA open or restart Orca. If skills get is unknown, explain that updating Orca restores the guide; use --help for read-only discovery and do not guess unsupported commands.

Frequently asked questions

What does the Orchestration AI skill do?

Why use Orchestration on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/stablyai/orca/tree/main/skills/orchestration. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Orchestration?

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 Orchestration?

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

Is the Orchestration AI skill free?

Yes. It is published on GitHub by stablyai 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Orca Orchestration

Resolve the CLI for this session

Load the version-matched guide before running Orca commands

Frequently asked questions

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