Q00/ouroboros
Agent OS: the agent gets smarter on its own. We just hold the line: Interview-gated, staged evaluation, budgeted evolution loop. MCP server, 14 runtimes: Claude Code, Codex CLI, Gemini CLI, OpenCode, Copilot, Kiro and more.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest 6 days ago, with 95 contributors on GitHub.
Peaked at #26 in the weekly ranking the week of May 3, its best in the past year.
Use Cases & Benefits
- Implements a specification-first AI development system that uses Socratic questioning and ontological analysis to clarify project goals before coding.
- Ensures clarity and reduces rework by evolving specifications through iterative questioning, evaluation, and convergence until stable ontologies are achieved.
- Use for refining ambiguous project ideas into precise, validated specifications before software development begins.
- Use for automating multi-stage AI-driven evaluation and evolution of software requirements to improve design accuracy.
- Use for integrating with Claude Code sessions to orchestrate AI agents that assist in complex decision-making and specification workflows.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
O U R O B O R O S
A Claude Code plugin that turns vague ideas into validated specs — before AI writes a single line of code.
AI can build anything. The hard part is knowing what to build.
Ouroboros is a specification-first AI development system. It applies Socratic questioning and ontological analysis to expose your hidden assumptions — before a single line of code is written.
Most AI coding fails at the input, not the output. The bottleneck isn't AI capability. It's human clarity. Ouroboros fixes the human, not the machine.
Wonder → "How should I live?" → "What IS 'live'?" → Ontology — Socrates
This is the philosophical engine behind Ouroboros. Every great question leads to a deeper question — and that deeper question is always ontological: not "how do I do this?" but "what IS this, really?"
This is not abstraction for its own sake. When you answer "What IS a task?" — deletable or archivable? solo or team? — you eliminate an entire class of rework. The ontological question is the most practical question.
Ouroboros embeds this into its architecture through the Double Diamond:
The first diamond is Socratic: diverge into questions, converge into ontological clarity. The second diamond is pragmatic: diverge into design options, converge into verified delivery. Each diamond requires the one before it — you cannot design what you haven't understood.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+942 stars over 84 days across 8 snapshot days; best day +17 on Sep 17.
Forks
635+100
Open issues
73+22
Compared with peers in AI Agents
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| vercel-labs/agent-desktop | 17.0K | +13.3K | 33 | today |
| thedotmack/claude-mem | 113.6K | +8.8K | 35 | today |
| stablyai/orca | 116.8K | +6.6K | 40 | today |
| milind-soni/OpenMausBot | 13.5K | +6.0K | 45 | today |
| HKUDS/DeepTutor | 55.5K | +5.5K | 65 | 5 days ago |
| Q00/ouroboros | 6.3K | — | 65 | 6 days ago |
| Category median | 55.5K | +6.6K | 40 | — |
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