{"categories":[{"label":"Build Tools","url":"https://skillfed.io/packages/category/software-development-build-tools/5"},{"label":"Code Generators","url":"https://skillfed.io/packages/category/software-development-code-generators"}],"enrichment":{"capability":"Ouroboros is an Agent OS that turns vague AI coding tasks into replayable, observable workflows by locking a specification before execution, then orchestrating multiple LLM runtimes (Claude Code, Codex, OpenCode, and others) through a structured interview-crystallize-execute-evaluate-evolve cycle.","skillfed_tags":["ai-agent-orchestration","llm-workflow-automation","spec-driven-development"],"use_cases":["Turn a vague product idea into a verified, working codebase by running a Socratic interview to lock the spec before any agent code generation.","Run the same AI coding workflow across multiple LLM runtimes (Claude, Codex, Gemini, etc.) with full auditability and replay capability.","Automate domain workflows like PR review, Jira ticket triage, or release management with scoped permissions and provenance tracking.","Reduce prompt engineering overhead by replacing manual QA with a three-stage automated evaluation gate that evolves the agent's behavior.","Integrate AI agents into CI/CD or incident-response pipelines where reproducibility and policy enforcement are non-negotiable."],"what_it_does":"Ouroboros is a local-first runtime layer that transforms non-deterministic AI coding work into deterministic, auditable workflows. Instead of ad-hoc prompting, it enforces a specification-first approach: a Socratic interview exposes hidden assumptions, an immutable seed spec locks intent before any code generation, and a three-stage automated evaluation gate replaces manual QA. The package orchestrates multiple LLM runtimes\u2014Claude Code, Codex CLI, OpenCode, Hermes, Gemini, and others\u2014through a unified contract, so the same workflow can run across different AI agents while remaining replayable and policy-bound.\n\nThe core stack splits into three layers: the OS kernel (this package) owns the contract and ledger; plugins add domain workflows (PR review, Jira sync, incident response); and a terminal shell (ourocode) provides a unified TUI. You can use Ouroboros standalone with any supported CLI, layer plugins for domain-specific tasks, or install the full stack for a unified cockpit. The package is actively maintained, supports Python 3.12\u20133.14, and carries no known vulnerabilities.","worth_installing":"Yes. Ouroboros is actively maintained, has low install friction, carries no known vulnerabilities, and solves a real problem\u2014turning vague AI tasks into deterministic, auditable workflows. The MIT license imposes no restrictions. Install it if you need structured, replayable AI coding workflows across multiple LLM runtimes; skip it if you only need ad-hoc prompting or single-agent integration."},"id":"ouroboros-ai","links":{"html":"https://skillfed.io/packages/ouroboros-ai","md":"https://skillfed.io/packages/ouroboros-ai.md","pypi":"https://pypi.org/project/ouroboros-ai/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-14","license_spdx":null,"license_treatment":"permissive","name":"ouroboros-ai","python_support":"supports_current","summary":"Pins an acceptance spec and omits any verify command or expected output from the worker's contract. Works with Claude Code, Codex CLI, OpenCode and 10 more runtimes."},"popularity":{"monthly_downloads":105045,"position":12724,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.51.5"}