By PeterFile
Orchestrate professional engineering workflows with specialized AI agents for code generation, structured specifications, test-driven development, and multi-agent task execution across Codex, Claude, and Gemini backends.
Execute codeagent-wrapper for multi-backend AI code tasks. Supports Codex, Claude, and Gemini backends with file references (@syntax) and structured output.
Execute Codex CLI for code analysis, refactoring, and automated code changes. Use when you need to delegate complex code tasks to Codex AI with file references (@syntax) and structured output.
Execute Gemini CLI for AI-powered code analysis and generation. Use when you need to leverage Google's Gemini models for complex reasoning tasks.
Create a Kiro spec for a feature in .kiro/specs create/update feature spec/PRD/RFC—requirements, design doc, and implementation tasks checklist.Trigger on spec/specification/PRD/RFC/tech spec, requirements/user story/acceptance criteria/EARS, design doc/architecture, task breakdown/implementation plan/checklist; 需求/验收/设计/任务.
Sync spec files with code changes. Triggers when modifying code that affects .kiro/specs/*/requirements.md or .kiro/specs/*/design.md. Use after implementing features, fixing bugs, or refactoring that changes behavior documented in specs.
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中文 | English
"亚瑟王的王者之剑已破石而出……你是否愿随王一同奔赴疆场?"
专为复杂软件工程任务设计的高保真 多代理编排系统。借鉴"圆桌会议"哲学,由 亚瑟王 (编排者) 协调专业代理,大规模地实现、评审并同步代码库变更。
设计哲学:通过 Spec-Driven Development 将需求拆解为原子任务,每个 Agent 只处理其上下文范围内的工作——无需理解全局,专注执行即可。任务分发给 Codex CLI (OpenAI) 和 Gemini CLI (Google) 等一线 Coding CLI,借力厂商的模型能力,而非重复造轮子去构建冗余的工具链和 sub-agent。
┌─────────────────────────────────────────────────────────────────┐
│ kiro-specs multi-agent-orchestrator │
│ ─────────── ──────────────────────── │
│ 需求 → 设计 → 任务 圆桌会议并行执行 tasks.md │
│ ↓ ↓ │
│ .kiro/specs/feature/tasks.md ──────→ AGENT_STATE.json │
└─────────────────────────────────────────────────────────────────┘
| 阶段 | 说明 |
|---|---|
| 1. 规范定义 | kiro-specs 引导创建 requirements → design → tasks |
| 2. 圆桌执行 | multi-agent-orchestrator 读取 tasks.md,分发给 Codex/Gemini (TDD) |
| 3. 评审闭环 | 每个任务经历 dispatch → review → fix → consolidate |
| 角色 | 代理 | 职责 |
|---|---|---|
| 亚瑟王 (King Arthur) | 编排者 | 规划、授权、质量门禁及项目状态同步。 |
| 高文 (Gawain) | 决策骑士 | 内环决策、严格的 JSON 输出及逻辑验证。 |
| Codex/Gemini | 执行者 | 分布式执行代码 (Codex) 与 UI (Gemini)。 |
| codeagent-wrapper | 执行层 | 驱动后端并行运行的 Go 运行时。 |
| 依赖项 | 版本 | 用途 |
|---|---|---|
| Node.js | 18+ | 运行 npx skills add |
| Python | 3.9+ | 编排脚本 |
| Go | 1.21+ | 编译 codeagent-wrapper |
| Claude Code/OpenCode | 最新版 | 触发技能 |
npx skills add PeterFile/devpilot-agents
此命令将本仓库的所有技能安装到你的代理环境中。
git clone https://github.com/PeterFile/devpilot-agents.git
cd devpilot-agents/codeagent-wrapper
go build -o codeagent-wrapper .
Windows:
go build -o codeagent-wrapper.exe .
Linux/macOS:
export PATH="$PWD:$PATH"
Windows (PowerShell):
$env:PATH = "$PWD;$env:PATH"
将代理定义复制到你的项目:
cp -r .opencode/agents/ <你的项目>/.opencode/agents/
或全局安装(对所有项目生效):
cp -r .opencode/agents/ ~/.config/opencode/agents/
这将添加 亚瑟王 (编排者) 和 高文 (决策骑士) 到你的 OpenCode 环境。
查看交互式流程图 - 点击逐步查看动画演示。
flowchart/ 目录包含源代码。本地运行:
cd flowchart
npm install
npm run dev
通过 codeagent-wrapper 调用 LLM 后端(默认 opencode),每轮迭代:
AGENT_STATE.json + PROJECT_PULSE.mddispatch_batch / dispatch_reviews 等动作| 变量 | 作用 | 默认值 |
|---|---|---|
CODEAGENT_OPENCODE_AGENT | 指定 OpenCode 使用的代理(可选) | OpenCode 默认 |
CODEAGENT_OPENCODE_MODEL | 覆盖 OpenCode 模型(可选) | OpenCode 配置 |
CODEAGENT_NO_TMUX | 禁用 tmux | Windows 自动设置 |
0:完成 | 1:停止/无进展 | 2:需人工决策在 Claude Code / OpenCode 中描述任务即可自动触发技能:
| 触发示例 | 技能 |
|---|---|
"Start orchestration from spec at .kiro/specs/my-feature" | multi-agent-orchestrator |
"Run orchestration for payment-integration" | multi-agent-orchestrator |
| "Create requirements for a new feature" | kiro-specs |
| "Help me write tests first" | test-driven-development |
| 技能 | 描述 |
|---|---|
| multi-agent-orchestrator | 从 Kiro 规范编排多代理工作流 |
| kiro-specs | 规范驱动工作流:需求 → 设计 → 任务 → 执行 |
| test-driven-development | 红-绿-重构 TDD 工作流 |
npx claudepluginhub peterfile/devpilot-agentsA bundled software delivery lifecycle toolkit for Claude Code: role-based agents (BA, Tech Lead, PM, Python dev, JS dev, QA, Personal Assistant) and composable skills (bug-fix workflow, feature planning, feature implementation, project seeding, code review, TDD, and more). Use when orchestrating an AI development team or when you want structured SDLC workflows inside a single project.
Orchestrate multi-agent teams for parallel code review, hypothesis-driven debugging, and coordinated feature development using Claude Code's Agent Teams
This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.
Portable Development System — AI-assisted development methodology with skills for consistency and agents for scale.
Persistent memory, shared standards, and structured workflows for AI coding agents. Detects project setup and injects agent context automatically.
General-purpose agent superteam for Claude code - contract-gated verification loops with 7 outer-loop roles, 5-phase orchestration, task form-driven inner-loop cooperation, and structural prevention of premature exits.