ouroboros

Source#

• Repository: Q00/ouroboros
• Last source update: 2026-06-07
• Last verified: 2026-06-07

Tags#

Integration notes#

Project-style implementation; treat as reference and extract bounded capabilities into dedicated workers.

worker.md example#

Starter worker.md contract mapped from this registry entry. Copy this file and adapt schemas, constraints, and statuses for your task.

---
id: ouroboros-repo-derived-worker
name: ouroboros Repo-Derived Worker
version: 1.0.0
source_registry_url: https://worker.md/registry/ouroboros/
source_repository: https://github.com/Q00/ouroboros
repository_default_branch: main
repository_language: Python
repository_license: MIT
repository_updated_at: 2026-06-07
worker_mode: agent-orchestration-worker
derivation_method: github_repository_metadata_plus_raw_readme
derivation_confidence: 0.95
derived_on: 2026-06-07
tags:
  - agent-os
  - ai-agent
  - llm-orchestration
  - llm-runtime
  - python
---

# ouroboros Repo-Derived Worker

## Repo-derived summary
- Registry summary: Agent OS: Stop prompting. Start specifying.
- Repository description: Agent OS: Stop prompting. Start specifying.
- Stars (snapshot): 4,447
- Primary language: Python
- Worker mode classification: agent-orchestration-worker

## Extracted from
- https://github.com/Q00/ouroboros
- https://github.com/Q00/ouroboros/blob/main/README.md
- https://github.com/Q00/ouroboros-plugins
- https://pi.dev/docs/latest/json
- https://github.com/Q00/ouroboros/issues

## Evidence notes (from repository text)
- README summary paragraph: Stop prompting. Start specifying. The Agent OS for replayable, specification-first AI coding workflows
- The Agent OS for replayable, specification-first AI coding workflows
- **Turn a vague idea into a verified, working codebase -- across Claude Code, Codex CLI, OpenCode, Hermes, Gemini, Kiro, Copilot, and Pi.**
- Ouroboros is an **Agent OS** for AI coding: a local-first runtime layer that
- turns non-deterministic agent work into a replayable, observable, policy-bound
- specification-first workflow: interview, crystallize, execute, evaluate,

## Installation hints found in README
- `pip install 'ouroboros-ai[claude]'`
- `pip install ouroboros-ai # base`
- `pip install ouroboros-ai[claude] # + Claude Code deps`
- `pip install ouroboros-ai[litellm] # + LiteLLM multi-provider`

## worker.md contract (derived starter)
Purpose: Execute one orchestrated agent task as a bounded worker step.

### Input schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "run_id",
    "task",
    "context"
  ],
  "properties": {
    "run_id": {
      "type": "string"
    },
    "task": {
      "type": "string"
    },
    "context": {
      "type": "object"
    }
  }
}
```

### Output schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "run_id",
    "status",
    "result"
  ],
  "properties": {
    "run_id": {
      "type": "string"
    },
    "status": {
      "type": "string",
      "enum": [
        "ok",
        "retryable_error",
        "invalid_request",
        "invalid_output"
      ]
    },
    "result": {
      "type": "object"
    }
  }
}
```

### Constraints
- timeout_seconds: 30
- max_attempts: 2
- idempotency_key: run_id
- status_enum: [ok, retryable_error, invalid_request, invalid_output]
- notes: adapt to concrete APIs/classes documented in this repository before production use

## How this should be used
1. Treat this file as a repo-derived starter profile, not a claim of an official repository API contract.
2. Replace schemas with exact interfaces from code/docs you adopt.
3. Keep execution bounded and auditable using worker protocol constraints.

How to use#

• Save this as a worker spec file (for example: ouroboros-my-task.worker.md).
• Replace the input/output schemas and purpose with your real bounded task.
• Enforce schema validation + timeout + retry policy in your runtime before production use.

Citation#

Reference URL: https://worker.md/registry/ouroboros/

Source URL: https://github.com/Q00/ouroboros