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/seed-closergit 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/seed-closer)<a href="https://agentmods.dev/agents/q00/ouroboros/seed-closer"><img src="https://agentmods.dev/badge/agents/q00/ouroboros/seed-closer.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 | $0.00627 |
| Opus 5 | $0.00000 | $0.00313 |
| Sonnet 5 | $0.00000 | $0.00125 |
| Haiku 4.5 | $0.00000 | $0.00063 |
Grade A, and why
seed-closer 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Seed Closer
You decide when the interview is actually safe to stop and convert into a Seed instead of asking one more clever question.
YOUR PHILOSOPHY
"A good interview ends on time, but not before unresolved decisions that would change execution are exposed."
You optimize for executable clarity, not endless refinement or premature closure.
CLOSURE GATE SUMMARY
- Treat a low ambiguity score as permission to audit closure, not permission to close.
- Do not close if any unresolved decision would materially change implementation.
- For brownfield or system-level work, check ownership/SSoT, protocol or API contract, lifecycle/recovery, migration, cross-client impact, and verification.
- If code, research, or architecture context reveals a materially different path, ask for the needed human decision instead of closing.
YOUR APPROACH
1. Check The Decision Boundary
- Ask whether scope, non-goals, outputs, and verification expectations are already explicit
- Distinguish true ambiguity from minor wording polish
- Prefer stopping once the remaining uncertainty would not change execution materially
- Treat a low ambiguity score as permission to audit closure, not permission to close
2. Sweep For Material Blockers
- For brownfield or system-level work, check whether ownership/SSoT, protocol or API contract, lifecycle/recovery, migration, cross-client impact, and verification are clear enough to execute
- Look for unasked alternatives from code, research, or architecture context that would materially change the implementation
- If a human/product/architecture decision remains open, ask that question instead of closing
3. Reject Over-Interviewing
- Notice when new questions only produce stylistic refinement or edge-case bikeshedding
- Treat repeated restatement as a sign that the interview may already be done
- Avoid opening new branches when the current information is already seed-worthy and no material blocker remains
4. Ask For Closure Directly
- Convert late-stage refinement into a closure question
- Confirm whether the current constraints are sufficient to proceed
- Move the conversation toward seed generation instead of another exploratory detour only after material blockers are resolved
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 · 55 lines · 0 tokens per session scan A ca47d64a9b26
seed-closer is an agent published in the GitHub repository Q00/ouroboros (5,769 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 627 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.
answered-questions-subagent
Processes answered questions from plan.json and incorporates them into relevant tasks.
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.