Q00/ouroboros is an Agent OS for running coding agents through interviews, staged evaluation, and repeated improvement cycles. It helps developers turn vague requests into tested code across multiple agent runtimes. Its catalogue add-ons provide workflows, agents, hooks, instructions, and integrations for operating those processes.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Q00/ouroboros --skill tutorialgit clone --depth 1 https://github.com/Q00/ouroborosWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/q00/ouroboros/tutorial)<a href="https://agentmods.dev/skills/q00/ouroboros/tutorial"><img src="https://agentmods.dev/badge/skills/q00/ouroboros/tutorial/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/q00/ouroboros/tutorial"><img src="https://agentmods.dev/badge/skills/q00/ouroboros/tutorial.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00010 | $0.00687 |
| Opus 5.5 | $0.00004 | $0.00275 |
| Sonnet 5.5 | $0.00002 | $0.00137 |
| Haiku 4.5 | $0.00001 | $0.00069 |
Grade A, and why
tutorial scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ouroboros:tutorial
Interactive tutorial that teaches Ouroboros through hands-on experience.
Usage
ooo tutorial
/ouroboros:tutorial
Principles
- Show something useful in the first 30 seconds.
- Learn by doing: the user answers questions about their own idea.
- Reveal features gradually.
- Always end a phase with one specific next action.
- Match the audience: technical users get the run, evaluate, and evolve details; non-technical users get the interview and plain language.
Flow (about 5 minutes)
-
Hook. Promise that in five minutes their vague idea becomes a precise specification, then ask what they want to build. If they have no idea, use a task-management CLI as the example.
-
Interview. Ask 3-4 Socratic questions about their idea (the problem it solves, the main users, the one feature that makes it useful now). Point out that each answer surfaced an assumption they had not stated.
-
Mini-Seed. Summarize their answers in Seed vocabulary:
Goal: <their goal, refined> Constraints: <2-3 constraints they named> Acceptance criteria: <2-3 checkable outcomes>Do not invent an ambiguity score. Explain that
ooo interviewmeasures ambiguity and continues until it is low enough to freeze a real Seed. -
The workflow.
Interview → Seed → Execute → Evaluate, with evaluation feeding back into the next Seed generation:ooo interview "your idea" # expose assumptions ooo seed # freeze the Seed ooo run # execute it ooo evaluate # verify against the acceptance criteria ooo status # check driftooo unstuckhelps when blocked.run,evaluate,evolve, andstatusneed the Ouroboros MCP server (ooo setup). -
Next step. Offer: start a real project (
ooo interview "your actual project idea"), the full reference (ooo help), or setup (ooo setup).
If the user asks how this differs from prompting an AI assistant directly:
without a spec, the assistant guesses and you rewrite the prompt until it
matches; with Ouroboros, the interview exposes hidden assumptions first, so the
build starts from an agreed Seed. If it seems complicated, three commands cover
most use: ooo interview, ooo seed, ooo run.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today Changed · -169 lines 8772faab3a55
- 3d ago Changed · +1 lines 0c35706189c9
- 1mo ago Changed · +10 lines 2cb8018fd454
- 1mo ago First seen · 231 lines · 10 tokens per session scan A 0fb6021d6279
tutorial is a skill published in the GitHub repository Q00/ouroboros (6,235 stars, last pushed today), licensed MIT. It adds 10 tokens to every session and 687 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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