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Ouroboros Config

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Q00
ouroboros-config

Open or drive the Ouroboros settings GUI (browser, TUI, or conversational fallback)

Overview

PublisherQ00
Repositoryouroboros
Skill nameouroboros-config
Stars
6K
Forks
605
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Q00 on GitHub. Read the source before you install it.

Installation

Install the Ouroboros Config 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/Q00/ouroboros.git /tmp/ouroboros
mkdir -p .claude/skills
cp -r /tmp/ouroboros/skills/config .claude/skills/ouroboros-config
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ouroboros Config 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 Ouroboros Config 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 Ouroboros Config 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.

/ouroboros:ouroboros-config

Settings for ~/.ouroboros/config.yaml: per-stage runtime/model selects, global runtime + LLM backend, install badges for missing CLIs, and env-override warnings.

Usage

ooo config
/ouroboros:ouroboros-config

Trigger keywords: "ooo config", "open settings", "configure ouroboros", "change model", "change agent"

Instructions

Pick the branch that matches where you (the agent) are running. The decisive question: can the user open a browser pointed at this machine?

Branch A — local harness (Claude Code / Codex on the user's own machine)

  1. Launch in the background (the command serves until stopped):

    bash
    if command -v ouroboros >/dev/null 2>&1; then
      ouroboros config
    else
      uvx --python '>=3.12' --from 'ouroboros-ai[tui]' ouroboros config
    fi

    The command detects the non-interactive context itself and serves the settings app over a local web server, auto-opening the user's browser. The uvx fallback is required for a Marketplace-plugin-only install, where the MCP server exists but ouroboros is not on PATH. In a development checkout use uv run ouroboros config.

  2. Relay the http://localhost:<port> line from the output so the user can open it manually if the browser did not pop up.

  3. Tell the user: edit → Save → then ask you to stop the server. Remind them a running MCP server may need a reconnect to pick up backend changes. Tell them they can reopen these settings any time with ooo config; saving a model choice never locks it permanently.

Branch B — remote host the user can reach over the network (SSH box, home server)

The user cannot see a browser opened here, but may be able to reach this host. Serve without auto-open and hand over the URL:

bash
ouroboros config --web --host 0.0.0.0 --no-browser

Relay the printed URL with this host's address substituted, plus the SSH tunnel fallback the command prints (ssh -L <port>:localhost:<port> <this-host>).

Branch C — chat gateway, no browser path at all (e.g. hermes driven from Discord)

Do NOT start a server nobody can reach. Drive the same settings conversationally over the scriptable surface:

  1. Show the current state:

    bash
    ouroboros config show
  2. Present the user a short menu in chat — default agent, per-stage agents, per-stage models — with the current values, and ask what to change.

  3. Apply each choice with the validated setter (same write path as the GUI):

    bash
    ouroboros config set orchestrator.runtime_backend <agent>
    ouroboros config set orchestrator.runtime_profile.stages.<interview|execute|evaluate|reflect> <agent>
    ouroboros config set clarification.default_model <model>        # interview & seed
    ouroboros config set execution.default_model <model>            # execute
    ouroboros config set evaluation.semantic_model <model>          # evaluate
    ouroboros config set resilience.reflect_model <model>           # reflect
    ouroboros config set llm.backend <backend>                      # internal LLM calls
  4. Confirm with ouroboros config show and summarize what changed.

If a set is rejected, relay the validation error verbatim — it lists the valid keys/values.

All branches

If the command fails with a missing-dependency hint, relay it verbatim (pip install 'ouroboros-ai[tui]'). Scriptable edits always remain on ouroboros config show|set|backend|init|validate.

End your final message with the state breadcrumb footer (RFC #1392), e.g.:

◆ Settings GUI serving at <url> → next: Save in browser, then stop the server
◆ Config updated via chat (<keys>) → next: reconnect MCP if the backend changed

RFC #1392 State Breadcrumb Footer

Your final response MUST end with exactly one breadcrumb footer line:

◆ <current state> → next: <recommended action>

Derive <current state> from live session state via ouroboros_session_status when that MCP projection is available; otherwise derive it from this skill's actual outcome. Never use a linear Step N of M footer because Ouroboros is an evolutionary loop. When the next action is genuinely a choice, list 2-3 honest options in the next: clause. The breadcrumb line must be the last line of the response.

Frequently asked questions

What does the Ouroboros Config AI skill do?

Open or drive the Ouroboros settings GUI (browser, TUI, or conversational fallback)

Why use Ouroboros Config on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Q00/ouroboros/tree/main/skills/config. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ouroboros Config?

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 Ouroboros Config?

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

Is the Ouroboros Config AI skill free?

Yes. It is published on GitHub by Q00 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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