Q00/ouroboros
Agent OS: the agent gets smarter on its own. We just hold the line: the grading command and expected result never make it into the success contract we hand it. Interview-gated, staged evaluation, budgeted evolution loop. MCP server, 13 runtimes: Claude Code, Codex CLI, Gemini CLI, OpenCode, Copilot, Kiro and more. observed · 2026-08-28
Health v2 · maintenance only
78/100
- Activity 99
- Release rhythm 87
- Longevity 16
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 1
- age_days: 232
- days_rel: 10
- days_push: 8
- n_releases_24m: 118
Adoption not part of the score
5687 stars · 569 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Ouroboros is an 'Agent OS' that manages AI coding agent workflows through interview-gated requirement capture, staged evaluation, and a budgeted evolution loop, keeping grading criteria hidden from the agent's success contract. It ships as a CLI (pip install ouroboros-ai) and MCP server/plugin supporting 13 coding agent runtimes including Claude Code, Codex CLI, Gemini CLI, OpenCode, and GitHub Copilot.
Use cases
- run AI coding agents in a verifiable spec-then-verify loop
- hide grading assertions from the agent so it cannot game evaluation
- turn a vague idea into a reviewed spec via an ambiguity-scoring interview
- orchestrate the same workflow across Claude Code, Codex, Gemini CLI and other runtimes
- evaluate and iterate on agent-generated code with staged verification
- record replayable evidence of AI coding work
When to choose
- you use coding agents like Claude Code or Codex and want trustworthy, spec-pinned verification of their output
- you want an agent loop that improves across generations without leaking the success criteria
- you need one orchestration engine across multiple agent runtimes
When to avoid
- you need a simple one-shot code generator without evaluation overhead
- you don't use any supported coding agent runtime
- you want a lightweight prompt library rather than a full workflow engine
Facets
cli-tool · maturity active
agent-framework llm-inference mcp cli developer-tools workflow-automation testing large-language-models developer-tools cli python cross-platform windows agent-os llm-orchestration agentic-ai claude-code codex-cli gemini-cli opencode github-copilot llm-evaluation coding-agent loop-engineering spec-driven-development interview-gated mcp-server self-improving-agent ai-agents automation command-line linux macos
4 sources
- readme: https://github.com/Q00/ouroboros · fetched 2026-08-28 · d1fa7d3b99ca
- homepage: https://ouroboros.page/ · fetched 2026-08-29 · 9a2867a80874
- site_page: https://ouroboros.page/learn/en/install · fetched 2026-08-29 · 529e3f343e94
- site_page: https://ouroboros.page/learn/en · fetched 2026-08-29 · 4589e7ac6e55
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Q00/ouroboros | main | 78 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem