痛苦： AI编程会话可能会丢失上下文，跳过审核，甚至在没有验证的情况下声称进度。

一个完整的工程团队集中在一个文件夹中。 一个团队将26名专业代理、20名技能、一名首席编排员和质量门组成，围绕基于文件的共享工作流程进行包装。为Claude Code、Codex CLI、Cursor、OpenCode和GitHub Copilot CLI设计——支持不同级别的钩子支持。

不是你自己配置的代理人市场。 为你自己的项目提供结构化的起点。

源自社区。 团队通过研究、使用并需要个性化多个优秀的开源代理项目而组建起来。该架构将每个项目中的最佳模式整合成一个单一的可移动基线。有关使此成为可能的项目，请参见致谢部分。

→ 视觉概述与现场演示

录制的第一次会话（逻辑剪枝前）（Windows一次性Python项目，2026-10-19;摘自初始化和早晨）：

入门指南 ·完整文档**

域名包 — 可以随A团队一起安装任何内容：

• builder-ai — LLM工程质量（评估、RAG、提示版本管理、安全）

A Team — A Complete Engineering Team in One Folder v1.4.1

The pain: AI coding sessions can lose context, skip reviews, and claim progress without verification.

A complete engineering team in one folder. A Team packages 26 specialist agents, 20 skills, a lead orchestrator, and quality gates around a shared file-based workflow. Designed for Claude Code, Codex CLI, Cursor, OpenCode, and GitHub Copilot CLI — with different levels of hook support.

Not a marketplace of agents you configure. A structured starting point for your own projects.

Born from the community. A Team was built by studying, using, and needing to personalise several excellent open-source agent projects. The architecture combines the best patterns from each into a single, portable baseline. See Acknowledgments for the projects that made this possible.

→ Visual overview & live demo

Recorded first session (before logical pruning) (Windows disposable Python project, 2026-10-19; excerpts from init and morning):

npx --yes @anthropic-ai/claude-code -p '/orchestrate init' --model sonnet --max-turns 12 --max-budget-usd 1 --permission-mode acceptEdits --permission-prompts none --output-format text
`/orchestrate init` is only partly done. The orchestrator wrote `.agent-sync/TEAM.md` and `.agent-sync/ROUTING.md`, but it deleted nothing.

npx --yes @anthropic-ai/claude-code -p '/orchestrate morning' --model sonnet --max-turns 12 --max-budget-usd 1 --permission-mode acceptEdits --permission-prompts none --output-format text
I've written today's plan to `.agent-sync/DAILY.md` and dispatched nothing. The morning plan needs your approval first.

Getting started · Full documentation**

Domain packs — install any alongside A Team:

• builder-ai — LLM engineering quality (evals, RAG, prompt versioning, safety)
• builder-design — AI UI design (states, streaming, accessibility, tokens)
• builder-product — Product quality gates (PRD, metrics, research synthesis, AI validation)
• builder-growth — Growth & messaging (positioning, copy, experiments, retention)

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What It Does

A Team turns any AI coding assistant into a structured, self-enforcing engineering team. Instead of one general-purpose model trying to do everything, you get:

• 26 specialist agents, each with a defined scope, model tier, and tool set
• 20 workflow skills that gate what can happen and when