Q00/ouroboros · integrations/dsh-plugin

Agent OS: the agent gets smarter on its own. We just hold the line: the grading command and expected result never make it into the success contract we hand it. Interview-gated, staged evaluation, budgeted evolution loop. MCP server, 13 runtimes: Claude Code, Codex CLI, Gemini CLI, OpenCode, Copilot, Kiro and more.

Bundle 已验证 MIT Python v0.51.7
Bundle 已验证

已收录

5519

Workflow

Bundle 已验证

★ 5,519 在 GitHub 查看
版本v0.51.7
语言Python
许可证MIT
在 GitHub 查看

预览

第 1 个预览,共 2 个:Q00/ouroboros · integrations/dsh-plugin
第 2 个预览,共 2 个:Q00/ouroboros · integrations/dsh-plugin

功能介绍

通过 DSH MCP 客户端挂载 Ouroboros 的纯配置包,在 DSH 中提供 36 个涵盖需求访谈、Seed、执行、评估与演化流程的工具。

适合

  • 希望通过 MCP 客户端在 DSH 中使用 Ouroboros 36 个工具、又不需要在配置包中加入自定义运行时代码的用户。
  • 开展结构化需求访谈、Seed 创建、执行、评估与迭代演化流程的团队。
  • 需要可重放、分阶段 Agent 工作流,而非单次非结构化编码提示的用户。

不适合

  • 不需要访谈、分阶段评估或演化循环的一次性简单任务。
  • 不希望在 DSH 中接入或操作 Ouroboros MCP 工作流的用户。
  • 需要独立界面功能的工作流;该配置包只通过 DSH MCP 客户端挂载 Ouroboros 工具。

README

English | 한국어 | 简体中文


◯ ─────────── ◯

Ouroboros

O U R O B O R O S

◯ ─────────── ◯

It gets smarter on its own. We just hold the line.

GitHub stars PyPI Tests License GitHub Sponsors

Q00%2Fouroboros | Trendshift

Quick Start · Why · Results · How It Works · Commands · Philosophy · Guide

curl -fsSL https://raw.githubusercontent.com/Q00/ouroboros/main/scripts/install.sh | OUROBOROS_INSTALL_REF=readme-hero bash

Terminal recording of the ouroboros CLI interview reporting an ambiguity score
Screen recording of the ChatGPT app calling Ouroboros as an integration
Screen recording of Claude Code running six Ouroboros interview advisory lanes in parallel
Screen recording of a Discord bot running the Ouroboros interview and reporting a final ambiguity of 0.15
Screen recording of DeepSeek Harness calling the Ouroboros interview tool and submitting advisory fan-out results
10x screen recording of Kiro CLI running an Ouroboros interview

Turn a vague idea into a verified, working codebase – across Claude Code, Codex CLI, OpenCode, Hermes, Gemini, Kiro, Copilot, Pi, Zcode, Goose, GJC, Antigravity, and Grok.

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 execution contract. It replaces ad-hoc prompting with a structured specification-first workflow: interview, crystallize, execute, evaluate, evolve.


The Ouroboros Agent OS Stack

Like any OS, Ouroboros is split into a stable OS layer of primitives, an application layer of domain workflows, and a shell that humans actually sit in front of. Three repos, one stack:

Layer Repo Role What it gives you
Shell (terminal client) Ouro-labs/ourocode Native terminal UI for running ooo workflows across Claude / Codex / Gemini CLIs in one session TUI, wonderTool decision pickers, MCP pane state, command discovery
Apps (domain workflows) Ouro-labs/ouroboros-plugins UserLevel plugin contract — composes core primitives into installable domain programs (PR ops, Jira sync, incidents, releases) Plugin manifest, scoped permissions, audit/provenance, reference plugins
OS (this repo) Q00/ouroboros Agent OS core — Seed, Ledger, Runtime, MCP, safety boundaries ooo commands, spec-first workflow engine, multi-runtime adapter

How they connect:

  ourocode  ──►  ooo / ouroboros-plugins  ──►  ouroboros core (Seed · Ledger · MCP · Runtime)
   shell             user-level apps                        kernel
  • The kernel (ouroboros) owns the contract: every action becomes a Seed-bound, ledger-recorded, replayable event — regardless of which LLM executes it.
  • Plugins (ouroboros-plugins) declare scoped capabilities against that contract, so domain workflows (review a PR, triage a Linear ticket, run a release) stay auditable and policy-bound instead of being one-off prompts.
  • Ourocode is the terminal shell: it surfaces MCP state, interview questions, and wonderTool decisions as first-class TUI elements, so you can drive the OS without leaving the keyboard or switching between CLIs.

Use ouroboros alone with any supported CLI, layer plugins on for domain workflows, or install ourocode when you want a unified terminal cockpit.

Disclaimer. The Ouroboros project and community are not affiliated with any cryptocurrency, token, memecoin, or trading community — including, but not limited to, any “ouroboros” tickers on pump.fun or other launchpads. This is an open-source developer tool. We do not issue, endorse, or hold any coins. Any token claiming association with this project is unauthorized.

Naming note. A separate, unaffiliated open-source project also uses the name “Ouroboros” — Anton Razzhigaev’s self-modifying, autonomous-memory agent at github.com/razzant/ouroboros. No shared code, no relationship. This project locks a specification before executing rather than rewriting its own architecture; if you’re looking for the latter, that’s the other one.


Why Ouroboros?

Most AI coding fails at the input, not the output. The bottleneck is not AI capability – it is human clarity.

Problem What Happens Ouroboros Fix
Vague prompts AI guesses, you rework Socratic interview exposes hidden assumptions
No spec Architecture drifts mid-build Immutable seed spec locks intent before code
Manual QA “Looks good” is not verification 3-stage automated evaluation gate

Quick Start

Install — one command, everything auto-detected:

curl -fsSL https://raw.githubusercontent.com/Q00/ouroboros/main/scripts/install.sh | OUROBOROS_INSTALL_REF=readme bash

First command — open your AI coding agent and run these in order:

> ooo setup
> ooo interview "I want to build a task management CLI"

ooo setup is a one-time configuration step. ooo interview is the first workflow command and starts the Socratic interview. After setup, Codex follows its currently selected model and Claude Code starts with its recommended model settings. Choose Directly configure models only when you want to pin a stage to a specific model; it opens the local settings screen in your browser. You can return to those settings any time with ooo config.

Or from a plain terminal, without an agent host:

$ ouroboros init start --orchestrator "I want to build a task management CLI tool"

Terminal recording of ouroboros setup refresh installing Codex rules and skills, Hermes skills, the OpenCode plugin and instruction guide, and the Pi and GJC bridges, ending with the line Refreshed runtime artifacts: codex, hermes, opencode, pi, gjc

Works with Claude Code, Codex CLI, GitHub Copilot CLI, OpenCode, Hermes, Gemini, Kiro CLI, Pi CLI, Zcode, Goose, GJC, Antigravity CLI, and Grok Build CLI. The installer detects available runtimes and registers the MCP server where the host supports it. For explicit selection, run ouroboros setup --runtime <opencode|kiro|copilot|gemini|pi|zcode|goose|gjc|antigravity|grok> after installation. Copilot live-discovers its subscription catalog via the GitHub Copilot models API; Kiro’s settings picker queries the authenticated CLI with kiro-cli chat --listmodels -f json, so account and enterprise allow-list changes appear without a hardcoded model table.

DeepSeek support. Ouroboros speaks DeepSeek two ways. Point the interview/Seed/QA pipeline at DeepSeek’s own models with --llm-backend dsh (ouroboros mcp serve --runtime claude-cli --llm-backend dsh, or OUROBOROS_LLM_BACKEND=dsh) — this drives DeepSeek Harness’s ACP server under the hood. Or go the other way: install the dsh-ouroboros plugin (dsh plugin --profile <your-profile> add "github:Q00/ouroboros#main&path:integrations/dsh-plugin") and type ooo interview / ooo auto directly in the DeepSeek Harness chat — the same ouroboros_interview / ouroboros_auto tools run natively inside it, Socratic questions and all. Both directions, including what the dsh backend needs beyond the one variable, are in the DeepSeek Harness guide.

常见问题常见问题

在启用了 DSH 的终端中执行已验证命令 dsh plugin --profile default add github:Q00/ouroboros#path:/integrations/dsh-plugin。命令会解析公开 package 元数据,并保持插件与本页展示的目录身份一致。