Ouroboros Open-Source Tool Forces AI Coding Agents to Clarify Specs Before Writing Code

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Ouroboros is an open-source, local-first runtime layer designed to address a common failure in AI-assisted coding: models making unchecked assumptions due to vague prompts. The tool sits in front of popular AI coding agents — including Claude Code, Codex CLI, and GitHub Copilot CLI — and replaces ad-hoc prompting with a structured five-stage workflow: interview, seed, execute, evaluate, and evolve. Before any code is generated, the system conducts a Socratic interview to surface hidden assumptions, then locks intent into an immutable specification only after ambiguity drops to 0.2 or below on a weighted clarity score. An automated three-stage evaluation gate checks output quality, while an evolutionary loop refines the specification across cycles until ontological similarity between consecutive generations reaches 0.95. The tool is installable via a single curl command and auto-detects the supported AI runtime in use.

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