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 unstuckgit 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/unstuck)<a href="https://agentmods.dev/skills/q00/ouroboros/unstuck"><img src="https://agentmods.dev/badge/skills/q00/ouroboros/unstuck.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 100 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00018 | $0.04593 |
| Opus 5 | $0.00009 | $0.02296 |
| Sonnet 5 | $0.00004 | $0.00919 |
| Haiku 4.5 | $0.00002 | $0.00459 |
Grade A, and why
unstuck 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 8d ago.
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 — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ouroboros:unstuck
Break through stagnation with lateral thinking personas. Two modes:
- Solo — one persona reframes the problem (fast, cheap).
- Debate — multiple personas run in parallel as sub-agents and the user picks the verdict (visual, thorough).
Usage
ooo lateral # debate (default) — all 5 lateral personas
ooo lateral <persona> # solo — single persona
ooo lateral debate <p1> <p2> ... # debate with explicit members
ooo lateral @<preset> # debate with preset (Phase 1: only @all = 5 personas)
Trigger keywords: "I'm stuck", "think sideways", "ooo lateral", "/ouroboros:unstuck".
Personas (Lateral Pool)
The lateral pool is stateless mindset personas only — five reframing lenses. Stateful roles (evaluator, qa-judge, ontologist, socratic-interviewer, etc.) are NOT mixed into this pool; they have their own SKILLs.
| Persona | Style | When to Use |
|---|---|---|
| hacker | "Make it work first, elegance later" | When overthinking blocks progress |
| researcher | "What information are we missing?" | When the problem is unclear |
| simplifier | "Cut scope, return to MVP" | When complexity is overwhelming |
| architect | "Restructure the approach entirely" | When the current design is wrong |
| contrarian | "What if we're solving the wrong problem?" | When assumptions need challenging |
When to Call
Direct user invocation — ooo lateral … from the prompt.
Autonomous chain from another SKILL — when you (the main session) are operating in another SKILL's persona (e.g., socratic-interviewer during ooo interview, or any agent role) and judge that the current question requires multi-perspective deliberation, you MAY invoke this SKILL on your own. No forced trigger; this is your self-assessment. After the debate, summarize the options for the user, return to the original SKILL's flow, and let the user decide. The user will see the sub-agent fan-out as it happens — that visibility is the point.
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.
- 8d ago First seen · 294 lines · 18 tokens per session scan A 40c3c561be9e
unstuck is a skill published in the GitHub repository Q00/ouroboros (5,789 stars, last pushed yesterday), licensed MIT. It adds 18 tokens to every session and 4,593 once invoked, about $0.0001 per session on Opus 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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auto-qa
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experiment
Experiment loop for iterative metric-driven code optimization using XLOOP.
ci-cd
A guide for designing automated build and delivery workflows with GitHub Actions. These workflows can run checks such as tests, code-quality scans, coverage checks, and builds when code is pushed or a pull request is opened.
metrics
North Star Metric, input metrics, and success dashboard design.
auto-fix
A bug-fixing workflow that first reproduces a problem with a test, then applies the smallest code change needed. It also checks the related code path and runs tests afterward.