ouroboros

Claude Code plugin only (no system package):

claude plugin marketplace add Q00/ouroboros && claude plugin install ouroboros@ouroboros

Then run ooo setup inside a Claude Code session.

pip / uv / pipx:

pip install ouroboros-ai                # base
pip install ouroboros-ai[claude]        # + Claude Code deps
pip install ouroboros-ai[litellm]       # + LiteLLM multi-provider
pip install ouroboros-ai[mcp]           # + MCP server/client support
pip install ouroboros-ai[tui]           # + Textual terminal UI
pip install ouroboros-ai[all]           # everything (claude + litellm + mcp + tui + dashboard)
ouroboros setup                         # configure runtime

Legacy compatibility: ouroboros-ai[dashboard] is still accepted as a compatibility alias while extras migrate.

See runtime guides: Claude Code · Codex CLI · OpenCode

Chat platform integration (OpenClaw / Slack / Discord):

clawhub install ouroboros                    # install OpenClaw skill
openclaw mcp set ouroboros '{"command":"uvx","args":["--from","ouroboros-ai[mcp]","ouroboros","mcp","serve"]}'

If openclaw mcp set is not recognized, run openclaw update to get the latest version.

Guide: Channel workflow integration

ouroboros uninstall

Removes all configuration, MCP registration, and data. See UNINSTALL.md for details.

Python >= 3.12 required. See pyproject.toml for the full dependency list.

What You Get

After one loop of the Ouroboros cycle, a vague idea becomes a verified codebase:

| Step | Before | After | |:-----|:-------|:------| | Interview | "Build me a task CLI" | 12 hidden assumptions exposed, ambiguity scored to 0.19 | | Seed | No spec | Immutable specification with acceptance criteria, ontology, constraints | | Evaluate | Manual review | 3-stage gate: Mechanical (free) -> Semantic -> Multi-Model Consensus |

interview  ->  Socratic questioning exposed 12 hidden assumptions
seed       ->  Crystallized answers into an immutable spec (Ambiguity: 0.15)
run        ->  Executed via Double Diamond decomposition
evaluate   ->  3-stage verification: Mechanical -> Semantic -> Consensus

Use ooo <cmd> inside your AI coding agent session, or ouroboros init start, ouroboros run seed.yaml, etc. from the terminal.

The serpent completed one loop. Each loop, it knows more than the last.

How It Compares

AI coding tools are powerful -- but they solve the wrong problem when the input is unclear.

| | Vanilla AI Coding | Ouroboros | |:--|:------------------|:---------| | Vague prompt | AI guesses intent, builds on assumptions | Socratic interview forces clarity before code | | Spec validation | No spec -- architecture drifts mid-build | Immutable seed spec locks intent; Ambiguity gate (<= 0.2) blocks premature code | | Evaluation | "Looks good" / manual QA | 3-stage automated gate: Mechanical -> Semantic -> Multi-Model Consensus | | Rework rate | High -- wrong assumptions surface late | Low -- assumptions surface in the interview, not in the PR review |

The Loop

The ouroboros -- a serpent devouring its own tail -- is not decoration. It IS the architecture:

    Interview -> Seed -> Execute -> Evaluate
        ^                           |
        +---- Evolutionary Loop ----+

Each cycle does not repeat -- it evolves. The output of evaluation feeds back as input for the next generation, until the system truly knows what it is 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 |

"This is where the Ouroboros eats its tail: the output of evaluation becomes the input for the next generation's seed specification." -- reflect.py

Convergence is reached when ontology similarity >= 0.95 -- when the system has questioned itself into clarity.

Ralph: The Loop That Never Stops

ooo ralph runs the evolutionary loop persistently -- across session boundaries -- until convergence is reached. Each step is stateless: the EventStore reconstructs the full lineage, so even if your machine restarts, the serpent picks up where it left off.

Ralph Cycle 1: evolve_step(lineage, seed) -> Gen 1 -> action=CONTINUE
Ralph Cycle 2: evolve_step(lineage)       -> Gen 2 -> action=CONTINUE
Ralph Cycle 3: evolve_step(lineage)       -> Gen 3 -> action=CONVERGED
                                                +-- Ralph stops.
                                                    The ontology has stabilized.

Commands

Inside AI coding agent sessions, use ooo <cmd> skills. From the terminal, use the ouroboros CLI.

| Skill (ooo) | CLI equivalent | What It Does | |:---------------|:---------------|:-------------| | ooo setup | ouroboros setup | Register runtime and configure project (one-time) | | ooo interview | ouroboros init start | Socratic questioning -- expose hidden assumptions | | ooo seed | (generated by interview) | Crystallize into immutable spec | | ooo run | ouroboros run seed.yaml | Execute via Double Diamond decomposition | | ooo evaluate | (via MCP) | 3-stage verification gate | | ooo evolve | (via MCP) | Evolutionary loop until ontology converges | | ooo unstuck | (via MCP) | 5 lateral thinking personas when you are stuck | | ooo status | ouroboros status executions / ouroboros status execution <id> | Session tracking + (MCP-only) drift detection | | ooo cancel | ouroboros cancel execution [<id>\|--all] | Cancel stuck or orphaned executions | | ooo ralph | (via MCP) | Persistent loop until verified | | ooo tutorial | (interactive) | Interactive hands-on learning | | ooo help | ouroboros --help | Full reference | | ooo pm | (via MCP) | PM-focused interview + PRD generation | | ooo qa | (via skill) | General-purpose QA verdict for any artifact | | ooo update | ouroboros update | Check for updates + upgrade to latest | | ooo brownfield | (via skill) | Scan and manage brownfield repo defaults | | ooo publish | (skill/runtime surface; uses gh CLI) | Publish a Seed as GitHub Epic/Task issues for team workflows |

Not all skills have direct CLI equivalents. Some (evaluate, evolve, unstuck, ralph, publish) are available through