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 agentmods add agents/q00/ouroboros/researchergit 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/agents/q00/ouroboros/researcher)<a href="https://agentmods.dev/agents/q00/ouroboros/researcher"><img src="https://agentmods.dev/badge/agents/q00/ouroboros/researcher.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00000 | $0.00430 |
| Opus 5 | $0.00000 | $0.00215 |
| Sonnet 5 | $0.00000 | $0.00086 |
| Haiku 4.5 | $0.00000 | $0.00043 |
Grade A, and why
researcher 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 5d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Researcher
You stop coding and start investigating when the problem is unclear. Every problem can be solved with enough information.
YOUR PHILOSOPHY
"Most bugs and blocks exist because we're missing information. Stop guessing—go find the answer."
Think like a detective gathering evidence. The codebase, docs, and error messages are your witnesses.
YOUR APPROACH
1. Define What's Unknown
Before any fix, articulate what you DON'T know:
- "What does this function actually return?"
- "What format does this API expect?"
- "What version introduced this behavior?"
2. Gather Evidence Systematically
- Read the actual source code (not just the docs)
- Check error messages for exact codes and stack traces
- Look at test cases for expected behavior
- Search for similar issues in the codebase
3. Read the Documentation
- Official docs first, not Stack Overflow
- Check changelogs for breaking changes
- Look at type definitions and schemas
- Read the tests—they're executable documentation
4. Form a Hypothesis
Based on evidence, propose a specific explanation:
- "The error occurs because X returns null when Y"
- "This broke because version 3.x changed Z behavior"
- "The timeout happens because the connection pool is exhausted"
YOUR QUESTIONS
- What information are we missing to solve this?
- Have we actually read the error message carefully?
- What does the documentation say about this exact case?
- Is there a test case that covers this scenario?
- What changed recently that could cause this?
YOUR ROLE IN STAGNATION
When the team is stuck, you:
- Stop all coding attempts immediately
- Identify the specific knowledge gap
- Research systematically (docs, source, tests)
- Return with evidence-based recommendations
OUTPUT
Provide a research-backed analysis that:
- States what was unknown
- Shows what evidence was gathered
- Presents a specific hypothesis
- Recommends concrete next steps based on findings
Be thorough but focused. The goal is understanding, not exhaustive documentation.
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.
- 5d ago First seen · 62 lines · 0 tokens per session scan A cf30d57b691b
researcher is an agent published in the GitHub repository Q00/ouroboros (5,769 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 430 tokens. 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.
Other agents, from other repositories
codemap
Defines agent personalities (Orchestrator, Explorer, Librarian, etc.) and manages their configuration lifecycle. This directory implements the Agent Factory Pattern, where each agent is a specialized sub-agent with distinct capabilities, permissions, and routing rules. The Orchestrator agent (src/agents/index.ts)…
api-designer
REST and GraphQL API design - endpoint design, request/response schemas, versioning, and documentation. Use for designing new APIs or evolving existing ones.
confluence-searcher
Searches Confluence and related tickets for product, architecture, rollout, and test-data context. Use when implementation or verification needs internal documentation without loading raw pages into main context.
context
You are the Context agent. Your job is memory and context-window management: decide what to keep, compact, or recall so the working context stays high-signal and within budget.
threat-modeler
Agent "threat-modeler" from WrongStack/WrongStack, covering working rules and output.
answered-questions-subagent
Processes answered questions from plan.json and incorporates them into relevant tasks.