Self-improving AI workflow system. Crystallize requirements before execution with Socratic interview, ambiguity scoring, and 3-stage evaluation.
Evaluate execution with three-stage verification pipeline
Start or monitor an evolutionary development loop
Full reference guide for Ouroboros commands and agents
Socratic interview to crystallize vague requirements
Persistent self-referential loop until verification passes
You see problems as structural, not just tactical. You question the foundation and redesign when the structure is wrong.
You question everything to uncover fundamental flaws in approach.
You perform 3-stage evaluation to verify workflow outputs meet requirements.
You find unconventional workarounds when the "right way" fails.
You perform ontological analysis to identify the essential nature of problems and solutions.
Evaluate execution with three-stage verification pipeline
Start or monitor an evolutionary development loop
Full reference guide for Ouroboros commands and agents
Socratic interview to crystallize vague requirements
Persistent self-referential loop until verification passes
Modifies files
Hook triggers on file write and edit operations
Uses power tools
Uses Bash, Write, or Edit tools
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◯ ─────────── ◯
O U R O B O R O S
◯ ─────────── ◯
Stop prompting. Start specifying.
A Codex-native workflow that turns vague ideas into validated specs — before AI writes a single line of code.
Quick Start · Philosophy · How · Commands · Agents
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?"
Wonder Ontology
💡 🔬
"What do I want?" → "What IS the thing I want?"
"Build a task CLI" → "What IS a task? What IS priority?"
"Fix the auth bug" → "Is this the root cause, or a symptom?"
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:
◇ Wonder ◇ Design
╱ (diverge) ╱ (diverge)
╱ explore ╱ create
╱ ╱
◆ ──────────── ◆ ──────────── ◆
╲ ╲
╲ define ╲ deliver
╲ (converge) ╲ (converge)
◇ Ontology ◇ Evaluation
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.
Step 1 — Set Codex auth (in your terminal):
export OPENAI_API_KEY="your-openai-key"
Step 2 — Install dependencies:
uv sync
Step 3 — Start building in a Codex session at this repo root:
ooo help
ooo interview "I want to build a task management CLI"
ooo seed
ooo run
Primary path docs: docs/running-with-codex.md
Claude-specific setup is still available as a compatibility path: docs/running-with-claude-code.md
ooo interview → Socratic questioning exposed 12 hidden assumptions
ooo seed → Crystallized answers into an immutable spec (Ambiguity: 0.15)
ooo run → Executed via Double Diamond decomposition
ooo evaluate → 3-stage verification: Mechanical → Semantic → Consensus
The serpent completed one loop. Each loop, it knows more than the last.
The ouroboros — a serpent devouring its own tail — isn't decoration. It IS the architecture:
Interview → Seed → Execute → Evaluate
↑ ↓
└──── Evolutionary Loop ────┘
Each cycle doesn't repeat — it evolves. The output of evaluation feeds back as input for the next generation, until the system truly knows what it's building.
| Phase | What Happens |
|---|---|
| Interview | Socratic questioning exposes hidden assumptions |
| Seed | Answers crystallize into an immutable specification |
| Execute | Double Diamond: Discover → Define → Design → Deliver |
| Evaluate | 3-stage gate: Mechanical ($0) → Semantic → Multi-Model Consensus |
| Evolve | Wonder ("What do we still not know?") → Reflect → next generation |
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Persistent file-based planning for AI coding agents. Crash-proof markdown plans (task_plan.md, findings.md, progress.md) that survive context loss and /clear, with an opt-in completion gate and multi-agent shared state. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard. Includes Arabic, German, Spanish, and Chinese (Simplified and Traditional).
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques