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refactor: research - move domain to repository root

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2026-07-09 04:01:30 +08:00
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docs/AGENTS.md
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## 目录用途
`docs/` 存放项目核心知识库文档，包含入门路径、核心概念与参考清单。
`docs/` 存放项目核心知识库文档，包含入门路径、核心概念、哲学方法论、参考清单和工作流。
根级 `research/` 承载新技术、优秀 repo 和工程范式研究；`docs/` 只保留到研究域的导航链接。
## 目录结构
@@ -13,7 +14,6 @@ docs/
├── getting-started/ # 从零开始、学习地图、环境与 AI CLI 配置
├── concepts/ # 索引 + 独立正文文档：核心概念、问题求解与工程思想
├── philosophy/ # 索引 + 独立正文文档：哲学方法论、思维模型与底层认知模型
├── research/ # 索引 + 独立正文文档：新技术、优秀 repo、工程范式和工具趋势研究
├── references/ # 索引 + 独立正文文档：工程实践、技术栈、清单与质量门禁
└── workflow/ # 索引 + 独立正文文档：开发流程、质量门禁、版本控制和文档同步
```
@@ -30,8 +30,8 @@ docs/
- `philosophy/AGENTS.md`：哲学方法论目录操作规则。
- `references/README.md`：参考资料索引，正文拆分到同目录模板、清单和技术栈文档。
- `references/AGENTS.md`：参考资料目录操作规则。
- `research/README.md`：研究索引，正文拆分到同目录研究笔记。
- `research/AGENTS.md`：研究笔记目录操作规则。
- `../research/README.md`：根级研究索引，正文拆分到研究对象目录或短篇研究笔记。
- `../research/AGENTS.md`：根级研究域操作规则。
- `workflow/README.md`：流程索引，正文拆分到同目录流程文档。
- `workflow/AGENTS.md`：开发流程目录操作规则。
@@ -73,7 +73,8 @@ docs/
## 维护规则
- 每个目录必须同时维护 `README.md` 和 `AGENTS.md`。
- 新增、删除、移动、重命名文档时，必须同步更新 `docs/README.md`、所在目录 README 索引和 `metadata/taxonomy.yml`。
- 新增、删除、移动、重命名 docs 文档时，必须同步更新 `docs/README.md`、所在目录 README 索引和 `metadata/taxonomy.yml`。
- 新增、删除、移动、重命名 research 文档时，必须同步更新根级 `research/README.md`、必要的 `docs/README.md` 跨入口、根 `README.md`、`metadata/taxonomy.yml` 和必要的 `metadata/redirects.yml`。
- 面向 AI 引用的重要入口变化，必须同步更新 `assets/ai-citation/llms-full.txt` 和相关摘要文件。
- 不确定信息标注 TODO，不用猜测补齐。
- 修改任意 docs README 后，运行 `make sync-doc-toc` 和 `make test`。
docs/README.md
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- 想理解 Vibe Coding 的底层概念，读 `concepts/`。
- 想补思维模型、软件工程常识和方法论，读 `philosophy/`。
- 想查工程模板、质量门禁、技术栈和常见坑，读 `references/`。
- 想记录新技术、优秀 repo 或工程趋势，读 `research/`。
- 想记录新技术、优秀 repo 或工程趋势，读根目录 `research/`。
- 想按标准流程推进任务、提交和推送，读 `workflow/`。
## 快速导航
@@ -17,7 +17,7 @@
| [concepts](./concepts/) | 核心概念、问题求解、关键词系统与工程思想 | [问题求解](./concepts/problem-solving.md) / [拼好码](./concepts/glue-coding.md) / [关键词系统](./concepts/keyword-system.md) |
| [philosophy](./philosophy/) | 哲学方法论、思维模型与底层认知模型 | [思维模型](./philosophy/thinking-models.md) / [方法论工具箱](./philosophy/methodology-toolbox.md) |
| [references](./references/) | 工程实践、技术栈、模板和检查清单 | [项目架构模板](./references/project-architecture-template.md) / [质量门禁](./references/quality-gates-and-pitfalls.md) |
| [research](./research/) | 新技术、优秀 repo 与工程范式研究 | [研究域治理契约](./research/research-domain-contract.md) / [研究迁移综合](./research/research-transfer-synthesis.md) |
| [research](../research/) | 根级研究域：新技术、优秀 repo 与工程范式研究 | [研究域治理契约](../research/research-domain-contract.md) / [研究迁移综合](../research/research-transfer-synthesis.md) |
| [workflow](./workflow/) | 开发流程、质量门禁和交付闭环 | [开发流程](./workflow/development-process.md) |
<details>
@@ -75,65 +75,65 @@
### research
- [README](./research/README.md) - 研究笔记索引。
- [研究域治理契约](./research/research-domain-contract.md) - 研究域的结构、raw 原始事实层、成熟度、证据、沉淀和归档规则。
- [研究价值与应用地图](./research/research-value-application-map.md) - 研究体系给用户带来的价值、核心启示、应用位置和下沉路线。
- [研究迁移综合](./research/research-transfer-synthesis.md) - 将对标拆解、改良迭代和杂交创新转成可执行研究路线。
- [Harness 研究对象](./research/harness/README.md) - Harness Engineering 的工程控制、评估器与反馈闭环研究对象。
- [Harness 工程解析](./research/harness/harness-engineering.md) - Harness Engineering 的工程控制、评估器与反馈闭环解析。
- [tmux 蜂群协作](./research/tmux-ai-swarm.md) - 用 tmux 让多个 AI 终端可感知、可调度、可救援的实验性协作范式。
- [Aider-AI/aider 研究域](./research/aider-ai-aider/README.md) - 终端 AI 结对编程工具。
- [Aider-AI/aider 研究分析](./research/aider-ai-aider/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [Aider-AI/aider 深度研究](./research/aider-ai-aider/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [cline/cline 研究域](./research/cline-cline/README.md) - IDE/SDK/CLI 自主编码 Agent。
- [cline/cline 研究分析](./research/cline-cline/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [cline/cline 深度研究](./research/cline-cline/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [hesreallyhim/awesome-claude-code 研究域](./research/hesreallyhim-awesome-claude-code/README.md) - Claude Code 生态索引。
- [hesreallyhim/awesome-claude-code 研究分析](./research/hesreallyhim-awesome-claude-code/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [hesreallyhim/awesome-claude-code 深度研究](./research/hesreallyhim-awesome-claude-code/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [openai/codex 研究域](./research/openai-codex/README.md) - 官方 coding agent 工具源码。
- [openai/codex 研究分析](./research/openai-codex/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [openai/codex 深度研究](./research/openai-codex/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [shanraisshan/claude-code-best-practice 研究域](./research/shanraisshan-claude-code-best-practice/README.md) - Claude Code / Agentic Engineering 最强对标。
- [shanraisshan/claude-code-best-practice 研究分析](./research/shanraisshan-claude-code-best-practice/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [shanraisshan/claude-code-best-practice 深度研究](./research/shanraisshan-claude-code-best-practice/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [tradecatlabs/vibe-coding-cn 研究域](./research/tradecatlabs-vibe-coding-cn/README.md) - 中文主线工程化工作流。
- [tradecatlabs/vibe-coding-cn 研究分析](./research/tradecatlabs-vibe-coding-cn/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [tradecatlabs/vibe-coding-cn 深度研究](./research/tradecatlabs-vibe-coding-cn/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [datawhalechina/easy-vibe 研究域](./research/datawhalechina-easy-vibe/README.md) - 中文分阶段交互式课程。
- [datawhalechina/easy-vibe 研究分析](./research/datawhalechina-easy-vibe/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [datawhalechina/easy-vibe 深度研究](./research/datawhalechina-easy-vibe/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [datawhalechina/vibe-vibe 研究域](./research/datawhalechina-vibe-vibe/README.md) - 中文零基础系统教程。
- [datawhalechina/vibe-vibe 研究分析](./research/datawhalechina-vibe-vibe/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [datawhalechina/vibe-vibe 深度研究](./research/datawhalechina-vibe-vibe/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [filipecalegario/awesome-vibe-coding 研究域](./research/filipecalegario-awesome-vibe-coding/README.md) - 国际 Vibe Coding 索引。
- [filipecalegario/awesome-vibe-coding 研究分析](./research/filipecalegario-awesome-vibe-coding/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [filipecalegario/awesome-vibe-coding 深度研究](./research/filipecalegario-awesome-vibe-coding/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [luzhenqian/ai-coding-lab 研究域](./research/luzhenqian-ai-coding-lab/README.md) - AI Coding 项目实验室。
- [luzhenqian/ai-coding-lab 研究分析](./research/luzhenqian-ai-coding-lab/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [luzhenqian/ai-coding-lab 深度研究](./research/luzhenqian-ai-coding-lab/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [ShouZhengAI/CS146S_CN 研究域](./research/shouzhengai-cs146s-cn/README.md) - 中文课程与 assignments。
- [ShouZhengAI/CS146S_CN 研究分析](./research/shouzhengai-cs146s-cn/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [ShouZhengAI/CS146S_CN 深度研究](./research/shouzhengai-cs146s-cn/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [ai-for-developers/awesome-vibe-coding 研究域](./research/ai-for-developers-awesome-vibe-coding/README.md) - 精选 Vibe Coding 资料清单。
- [ai-for-developers/awesome-vibe-coding 研究分析](./research/ai-for-developers-awesome-vibe-coding/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [ai-for-developers/awesome-vibe-coding 深度研究](./research/ai-for-developers-awesome-vibe-coding/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [Daotin/ai-coding 研究域](./research/daotin-ai-coding/README.md) - AI Coding 经验汇总。
- [Daotin/ai-coding 研究分析](./research/daotin-ai-coding/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [Daotin/ai-coding 深度研究](./research/daotin-ai-coding/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [earyantLe/vibe-coding-skill 研究域](./research/earyantle-vibe-coding-skill/README.md) - Vibe Coding Skill / SOP 化。
- [earyantLe/vibe-coding-skill 研究分析](./research/earyantle-vibe-coding-skill/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [earyantLe/vibe-coding-skill 深度研究](./research/earyantle-vibe-coding-skill/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [liyupi/ai-guide 研究域](./research/liyupi-ai-guide/README.md) - AI 资源大全与产品实用路线。
- [liyupi/ai-guide 研究分析](./research/liyupi-ai-guide/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [liyupi/ai-guide 深度研究](./research/liyupi-ai-guide/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [RooCodeInc/Roo-Code 研究域](./research/roocodeinc-roo-code/README.md) - 已归档多 Agent 编辑器工具。
- [RooCodeInc/Roo-Code 研究分析](./research/roocodeinc-roo-code/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [RooCodeInc/Roo-Code 深度研究](./research/roocodeinc-roo-code/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [wendy7756/vibe-coding-guide 研究域](./research/wendy7756-vibe-coding-guide/README.md) - 非程序员自然语言编程指南。
- [wendy7756/vibe-coding-guide 研究分析](./research/wendy7756-vibe-coding-guide/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [wendy7756/vibe-coding-guide 深度研究](./research/wendy7756-vibe-coding-guide/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [AGENTS](./research/AGENTS.md) - 研究笔记目录操作规则。
- [README](../research/README.md) - 研究笔记索引。
- [研究域治理契约](../research/research-domain-contract.md) - 研究域的结构、raw 原始事实层、成熟度、证据、沉淀和归档规则。
- [研究价值与应用地图](../research/research-value-application-map.md) - 研究体系给用户带来的价值、核心启示、应用位置和下沉路线。
- [研究迁移综合](../research/research-transfer-synthesis.md) - 将对标拆解、改良迭代和杂交创新转成可执行研究路线。
- [Harness 研究对象](../research/harness/README.md) - Harness Engineering 的工程控制、评估器与反馈闭环研究对象。
- [Harness 工程解析](../research/harness/harness-engineering.md) - Harness Engineering 的工程控制、评估器与反馈闭环解析。
- [tmux 蜂群协作](../research/tmux-ai-swarm.md) - 用 tmux 让多个 AI 终端可感知、可调度、可救援的实验性协作范式。
- [Aider-AI/aider 研究域](../research/aider-ai-aider/README.md) - 终端 AI 结对编程工具。
- [Aider-AI/aider 研究分析](../research/aider-ai-aider/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [Aider-AI/aider 深度研究](../research/aider-ai-aider/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [cline/cline 研究域](../research/cline-cline/README.md) - IDE/SDK/CLI 自主编码 Agent。
- [cline/cline 研究分析](../research/cline-cline/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [cline/cline 深度研究](../research/cline-cline/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [hesreallyhim/awesome-claude-code 研究域](../research/hesreallyhim-awesome-claude-code/README.md) - Claude Code 生态索引。
- [hesreallyhim/awesome-claude-code 研究分析](../research/hesreallyhim-awesome-claude-code/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [hesreallyhim/awesome-claude-code 深度研究](../research/hesreallyhim-awesome-claude-code/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [openai/codex 研究域](../research/openai-codex/README.md) - 官方 coding agent 工具源码。
- [openai/codex 研究分析](../research/openai-codex/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [openai/codex 深度研究](../research/openai-codex/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [shanraisshan/claude-code-best-practice 研究域](../research/shanraisshan-claude-code-best-practice/README.md) - Claude Code / Agentic Engineering 最强对标。
- [shanraisshan/claude-code-best-practice 研究分析](../research/shanraisshan-claude-code-best-practice/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [shanraisshan/claude-code-best-practice 深度研究](../research/shanraisshan-claude-code-best-practice/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [tradecatlabs/vibe-coding-cn 研究域](../research/tradecatlabs-vibe-coding-cn/README.md) - 中文主线工程化工作流。
- [tradecatlabs/vibe-coding-cn 研究分析](../research/tradecatlabs-vibe-coding-cn/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [tradecatlabs/vibe-coding-cn 深度研究](../research/tradecatlabs-vibe-coding-cn/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [datawhalechina/easy-vibe 研究域](../research/datawhalechina-easy-vibe/README.md) - 中文分阶段交互式课程。
- [datawhalechina/easy-vibe 研究分析](../research/datawhalechina-easy-vibe/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [datawhalechina/easy-vibe 深度研究](../research/datawhalechina-easy-vibe/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [datawhalechina/vibe-vibe 研究域](../research/datawhalechina-vibe-vibe/README.md) - 中文零基础系统教程。
- [datawhalechina/vibe-vibe 研究分析](../research/datawhalechina-vibe-vibe/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [datawhalechina/vibe-vibe 深度研究](../research/datawhalechina-vibe-vibe/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [filipecalegario/awesome-vibe-coding 研究域](../research/filipecalegario-awesome-vibe-coding/README.md) - 国际 Vibe Coding 索引。
- [filipecalegario/awesome-vibe-coding 研究分析](../research/filipecalegario-awesome-vibe-coding/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [filipecalegario/awesome-vibe-coding 深度研究](../research/filipecalegario-awesome-vibe-coding/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [luzhenqian/ai-coding-lab 研究域](../research/luzhenqian-ai-coding-lab/README.md) - AI Coding 项目实验室。
- [luzhenqian/ai-coding-lab 研究分析](../research/luzhenqian-ai-coding-lab/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [luzhenqian/ai-coding-lab 深度研究](../research/luzhenqian-ai-coding-lab/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [ShouZhengAI/CS146S_CN 研究域](../research/shouzhengai-cs146s-cn/README.md) - 中文课程与 assignments。
- [ShouZhengAI/CS146S_CN 研究分析](../research/shouzhengai-cs146s-cn/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [ShouZhengAI/CS146S_CN 深度研究](../research/shouzhengai-cs146s-cn/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [ai-for-developers/awesome-vibe-coding 研究域](../research/ai-for-developers-awesome-vibe-coding/README.md) - 精选 Vibe Coding 资料清单。
- [ai-for-developers/awesome-vibe-coding 研究分析](../research/ai-for-developers-awesome-vibe-coding/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [ai-for-developers/awesome-vibe-coding 深度研究](../research/ai-for-developers-awesome-vibe-coding/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [Daotin/ai-coding 研究域](../research/daotin-ai-coding/README.md) - AI Coding 经验汇总。
- [Daotin/ai-coding 研究分析](../research/daotin-ai-coding/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [Daotin/ai-coding 深度研究](../research/daotin-ai-coding/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [earyantLe/vibe-coding-skill 研究域](../research/earyantle-vibe-coding-skill/README.md) - Vibe Coding Skill / SOP 化。
- [earyantLe/vibe-coding-skill 研究分析](../research/earyantle-vibe-coding-skill/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [earyantLe/vibe-coding-skill 深度研究](../research/earyantle-vibe-coding-skill/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [liyupi/ai-guide 研究域](../research/liyupi-ai-guide/README.md) - AI 资源大全与产品实用路线。
- [liyupi/ai-guide 研究分析](../research/liyupi-ai-guide/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [liyupi/ai-guide 深度研究](../research/liyupi-ai-guide/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [RooCodeInc/Roo-Code 研究域](../research/roocodeinc-roo-code/README.md) - 已归档多 Agent 编辑器工具。
- [RooCodeInc/Roo-Code 研究分析](../research/roocodeinc-roo-code/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [RooCodeInc/Roo-Code 深度研究](../research/roocodeinc-roo-code/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [wendy7756/vibe-coding-guide 研究域](../research/wendy7756-vibe-coding-guide/README.md) - 非程序员自然语言编程指南。
- [wendy7756/vibe-coding-guide 研究分析](../research/wendy7756-vibe-coding-guide/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [wendy7756/vibe-coding-guide 深度研究](../research/wendy7756-vibe-coding-guide/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [AGENTS](../research/AGENTS.md) - 研究笔记目录操作规则。
### workflow
@@ -150,7 +150,7 @@
- 已经有项目问题：先读 [问题求解](./concepts/problem-solving.md)，再读 [质量门禁与常见坑](./references/quality-gates-and-pitfalls.md)。
- 需要给 AI Agent 上下文：先给它 [AGENTS](./AGENTS.md)，再给它当前任务对应目录的 README 和具体正文文档。
- 需要规范执行顺序：读 [开发流程](./workflow/development-process.md)。
- 新增内容时，先判断它属于教程、概念、哲学、参考还是研究，再放入对应目录的独立文档。
- 新增内容时，先判断它属于教程、概念、哲学、参考还是研究；研究内容进入根目录 `research/`。
## 正文
docs/concepts/AGENTS.md
+1 -1
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@@ -38,5 +38,5 @@ concepts/
- 每个概念先说明它解决的问题。
- 尽量给出使用场景、判断标准和简单例子。
- 不确定的外部事实必须标注 TODO，或放入 `docs/research/` 等待验证。
- 不确定的外部事实必须标注 TODO，或放入 `research/` 等待验证。
- 修改后必须运行 `make sync-doc-toc` 和 `make test`。
docs/references/AGENTS.md
+1 -1
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@@ -36,7 +36,7 @@ references/
- 新增参考资料时，优先写入对应独立主题文档，并同步更新 `README.md` 索引。
- 检查清单、模板、质量门禁和经验类内容优先进入对应独立文档，避免重新塞回 README。
- 技术选型、技术栈组合和学习路径优先维护在 `technology-stack.md`。
- 不在本目录写一次性研究笔记；新技术判断应先放入 `docs/research/`。
- 不在本目录写一次性研究笔记；新技术判断应先放入 `research/`。
- 不在 README 正文中写 `和其他目录的边界` 或 `维护规则`；维护者规则只写本文件。
## 质量要求
docs/research/AGENTS.md
-128
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@@ -1,128 +0,0 @@
# Research 目录 Agent 指南
## 目录职责
`docs/research/` 存放新技术、新技术栈、优秀 repo、工程范式和工具趋势的研究对象与短篇研究。
这里的文档回答：
- 它是什么。
- 它解决什么问题。
- 为什么值得关注。
- 适合什么场景。
- 有什么风险和替代方案。
## 文件地图
```text
research/
├── README.md # 索引入口：研究对象与研究笔记导航
├── research-domain-contract.md # 研究域治理契约：结构、分层、成熟度、证据和归档规则
├── research-value-application-map.md # 研究价值与应用地图：用户价值、核心启示和下沉路线
├── research-transfer-synthesis.md # 研究迁移综合：对标拆解、改良迭代、杂交创新和验证动作
├── harness/
│ ├── README.md
│ ├── harness-engineering.md
│ └── AGENTS.md
├── ai-for-developers-awesome-vibe-coding/
│ ├── README.md
│ ├── domain.yml
│ ├── analysis.md
│ ├── raw/
│ └── AGENTS.md
├── aider-ai-aider/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── cline-cline/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── daotin-ai-coding/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── datawhalechina-easy-vibe/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── datawhalechina-vibe-vibe/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── earyantle-vibe-coding-skill/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── filipecalegario-awesome-vibe-coding/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── hesreallyhim-awesome-claude-code/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── liyupi-ai-guide/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── luzhenqian-ai-coding-lab/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── openai-codex/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── roocodeinc-roo-code/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── shanraisshan-claude-code-best-practice/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── shouzhengai-cs146s-cn/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── tradecatlabs-vibe-coding-cn/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── wendy7756-vibe-coding-guide/
│ ├── README.md
│ ├── domain.yml
│ └── AGENTS.md
├── tmux-ai-swarm.md
└── AGENTS.md # 本目录操作规则
```
上方只展开了第一个外部仓库研究域的基础形态；所有外部仓库研究域都必须包含同样的原始事实层、
`analysis.md` 和 `deep-dive.md`。
`deep-dive.md` 是 L2 产物；当前 17 个外部仓库研究域已经全部补齐，P3 只表示采用优先级低，
不再表示研究深度缺口。
## 修改规则
- 继承 `docs/AGENTS.md` 的 README 结构契约：H1 后直接进入 `## 字多不看`，再按 `快速导航 -> 完整细粒度目录 -> 使用方式 -> 正文` 排列。
- 长期研究域必须遵循 `research-domain-contract.md`；外部仓库研究域至少包含 `README.md`、`AGENTS.md`、`domain.yml` 和 `raw/`。
- 长期研究对象优先使用独立目录；目录内必须包含 `README.md` 和 `AGENTS.md`。
- 外部仓库研究对象采用“一仓库一研究域”，目录名使用 `<owner>-<repo>` 的小写短横线形式。
- `raw/` 是原始事实层，只保存拉取到本地的一手材料；分析判断写入上一级 `README.md`、`analysis.md` 或 `decisions.md`。
- `research-value-application-map.md` 是研究体系的转化入口，用于说明研究给用户带来的价值、启示、应用位置和下沉路线。
- `research-transfer-synthesis.md` 是横向迁移入口，用于把研究对象拆成机制、迁移边界、改良动作和验证指标。
- GitHub 仓库 raw 层通过 `python3 scripts/fetch-research-raw.py` 刷新；不要手工改写 `*.raw.*` 文件。
- 单次短篇观察可以先写成独立 `.md` 文档；如果对象会持续演化，应迁入对象目录。
- 新增研究对象目录或研究 `.md` 文件时，必须同步更新 `README.md`、`metadata/taxonomy.yml` 和必要的 `redirects.yml`。
- 研究内容稳定后，放入 `docs/concepts/`、`docs/references/` 或 `docs/philosophy/` 的对应章节。
- 外部项目、模型、工具、版本和事实状态可能变化，涉及最新信息时必须核验来源。
- 不在 README 正文中写 `和其他目录的边界` 或 `维护规则`；维护者规则只写本文件。
## 质量要求
- 不写新闻转述，要给出判断、边界、采用建议和后续观察点。
- L2 研究不能只写“可借鉴点”，必须写清对标拆解、可迁移做法、不可迁移条件、下一步试用动作和验证指标。
- 对不确定信息标注“待验证”或 TODO。
- 引入外部事实时优先引用官方文档、原始仓库、论文或可信一手来源。
- 修改后必须运行 `make sync-doc-toc` 和 `make test`。
docs/research/README.md
-113
View File
@@ -1,113 +0,0 @@
# 研究
## 字多不看
- 本目录记录新技术、优秀 repo、工程范式和工具趋势的研究对象。
- 新增或重构长期研究对象时，先遵循研究域治理契约，并拉取 raw 原始事实层。
- 长期研究对象优先使用独立目录，短篇观察可先用单文件承载。
- 外部仓库研究对象采用“一仓库一研究域”，不再使用聚合目录承载多个仓库。
- 成熟后可沉淀到 concepts、references、workflow 或 skills。
## 快速导航
| 文档 | 定位 |
|:---|:---|
| <a id="research-domain-contract"></a>[研究域治理契约](research-domain-contract.md) | 研究域的结构、raw 原始事实层、成熟度、证据、沉淀和归档规则。 |
| <a id="research-value-application-map"></a>[研究价值与应用地图](research-value-application-map.md) | 研究体系给用户带来的价值、核心启示、应用位置和下沉路线。 |
| <a id="research-transfer-synthesis"></a>[研究迁移综合](research-transfer-synthesis.md) | 将对标拆解、改良迭代和杂交创新转成可执行研究路线。 |
| <a id="research-harness-engineering"></a>[Harness 研究对象](harness/) | 工程控制、评估器、反馈闭环与 AI 生成系统可靠性。 |
| <a id="research-tmux-ai-swarm"></a>[tmux 蜂群协作](tmux-ai-swarm.md) | 用 tmux 让多个 AI 终端可感知、可调度、可救援的实验性协作范式。 |
| <a id="research-aider-ai-aider"></a>[Aider-AI/aider 研究域](aider-ai-aider/) | 终端 AI 结对编程工具。 |
| <a id="research-cline-cline"></a>[cline/cline 研究域](cline-cline/) | IDE/SDK/CLI 自主编码 Agent。 |
| <a id="research-hesreallyhim-awesome-claude-code"></a>[hesreallyhim/awesome-claude-code 研究域](hesreallyhim-awesome-claude-code/) | Claude Code 生态索引。 |
| <a id="research-openai-codex"></a>[openai/codex 研究域](openai-codex/) | 官方 coding agent 工具源码。 |
| <a id="research-shanraisshan-claude-code-best-practice"></a>[shanraisshan/claude-code-best-practice 研究域](shanraisshan-claude-code-best-practice/) | Claude Code / Agentic Engineering 最强对标。 |
| <a id="research-tradecatlabs-vibe-coding-cn"></a>[tradecatlabs/vibe-coding-cn 研究域](tradecatlabs-vibe-coding-cn/) | 中文主线工程化工作流。 |
| <a id="research-datawhalechina-easy-vibe"></a>[datawhalechina/easy-vibe 研究域](datawhalechina-easy-vibe/) | 中文分阶段交互式课程。 |
| <a id="research-datawhalechina-vibe-vibe"></a>[datawhalechina/vibe-vibe 研究域](datawhalechina-vibe-vibe/) | 中文零基础系统教程。 |
| <a id="research-filipecalegario-awesome-vibe-coding"></a>[filipecalegario/awesome-vibe-coding 研究域](filipecalegario-awesome-vibe-coding/) | 国际 Vibe Coding 索引。 |
| <a id="research-luzhenqian-ai-coding-lab"></a>[luzhenqian/ai-coding-lab 研究域](luzhenqian-ai-coding-lab/) | AI Coding 项目实验室。 |
| <a id="research-shouzhengai-cs146s-cn"></a>[ShouZhengAI/CS146S_CN 研究域](shouzhengai-cs146s-cn/) | 中文课程与 assignments。 |
| <a id="research-ai-for-developers-awesome-vibe-coding"></a>[ai-for-developers/awesome-vibe-coding 研究域](ai-for-developers-awesome-vibe-coding/) | 精选 Vibe Coding 资料清单。 |
| <a id="research-daotin-ai-coding"></a>[Daotin/ai-coding 研究域](daotin-ai-coding/) | AI Coding 经验汇总。 |
| <a id="research-earyantle-vibe-coding-skill"></a>[earyantLe/vibe-coding-skill 研究域](earyantle-vibe-coding-skill/) | Vibe Coding Skill / SOP 化。 |
| <a id="research-liyupi-ai-guide"></a>[liyupi/ai-guide 研究域](liyupi-ai-guide/) | AI 资源大全与产品实用路线。 |
| <a id="research-roocodeinc-roo-code"></a>[RooCodeInc/Roo-Code 研究域](roocodeinc-roo-code/) | 已归档多 Agent 编辑器工具；当前已归档，仅作参考。 |
| <a id="research-wendy7756-vibe-coding-guide"></a>[wendy7756/vibe-coding-guide 研究域](wendy7756-vibe-coding-guide/) | 非程序员自然语言编程指南。 |
<details>
<summary><strong>完整细粒度目录（点击展开/收起）</strong></summary>
### 细粒度目录
- [研究域治理契约](research-domain-contract.md) - 研究域的结构、raw 原始事实层、成熟度、证据、沉淀和归档规则。
- [研究价值与应用地图](research-value-application-map.md) - 研究体系给用户带来的价值、核心启示、应用位置和下沉路线。
- [研究迁移综合](research-transfer-synthesis.md) - 将对标拆解、改良迭代和杂交创新转成可执行研究路线。
- [Harness 研究对象](harness/README.md) - 工程控制、评估器、反馈闭环与 AI 生成系统可靠性。
- [Harness 工程解析](harness/harness-engineering.md) - Harness Engineering 的工程控制、评估器与反馈闭环解析。
- [tmux 蜂群协作](tmux-ai-swarm.md) - 用 tmux 让多个 AI 终端可感知、可调度、可救援的实验性协作范式。
- [Aider-AI/aider 研究域](aider-ai-aider/README.md) - 终端 AI 结对编程工具。
- [Aider-AI/aider 研究分析](aider-ai-aider/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [Aider-AI/aider 深度研究](aider-ai-aider/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [cline/cline 研究域](cline-cline/README.md) - IDE/SDK/CLI 自主编码 Agent。
- [cline/cline 研究分析](cline-cline/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [cline/cline 深度研究](cline-cline/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [hesreallyhim/awesome-claude-code 研究域](hesreallyhim-awesome-claude-code/README.md) - Claude Code 生态索引。
- [hesreallyhim/awesome-claude-code 研究分析](hesreallyhim-awesome-claude-code/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [hesreallyhim/awesome-claude-code 深度研究](hesreallyhim-awesome-claude-code/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [openai/codex 研究域](openai-codex/README.md) - 官方 coding agent 工具源码。
- [openai/codex 研究分析](openai-codex/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [openai/codex 深度研究](openai-codex/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [shanraisshan/claude-code-best-practice 研究域](shanraisshan-claude-code-best-practice/README.md) - Claude Code / Agentic Engineering 最强对标。
- [shanraisshan/claude-code-best-practice 研究分析](shanraisshan-claude-code-best-practice/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [shanraisshan/claude-code-best-practice 深度研究](shanraisshan-claude-code-best-practice/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [tradecatlabs/vibe-coding-cn 研究域](tradecatlabs-vibe-coding-cn/README.md) - 中文主线工程化工作流。
- [tradecatlabs/vibe-coding-cn 研究分析](tradecatlabs-vibe-coding-cn/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [tradecatlabs/vibe-coding-cn 深度研究](tradecatlabs-vibe-coding-cn/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [datawhalechina/easy-vibe 研究域](datawhalechina-easy-vibe/README.md) - 中文分阶段交互式课程。
- [datawhalechina/easy-vibe 研究分析](datawhalechina-easy-vibe/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [datawhalechina/easy-vibe 深度研究](datawhalechina-easy-vibe/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [datawhalechina/vibe-vibe 研究域](datawhalechina-vibe-vibe/README.md) - 中文零基础系统教程。
- [datawhalechina/vibe-vibe 研究分析](datawhalechina-vibe-vibe/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [datawhalechina/vibe-vibe 深度研究](datawhalechina-vibe-vibe/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [filipecalegario/awesome-vibe-coding 研究域](filipecalegario-awesome-vibe-coding/README.md) - 国际 Vibe Coding 索引。
- [filipecalegario/awesome-vibe-coding 研究分析](filipecalegario-awesome-vibe-coding/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [filipecalegario/awesome-vibe-coding 深度研究](filipecalegario-awesome-vibe-coding/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [luzhenqian/ai-coding-lab 研究域](luzhenqian-ai-coding-lab/README.md) - AI Coding 项目实验室。
- [luzhenqian/ai-coding-lab 研究分析](luzhenqian-ai-coding-lab/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [luzhenqian/ai-coding-lab 深度研究](luzhenqian-ai-coding-lab/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [ShouZhengAI/CS146S_CN 研究域](shouzhengai-cs146s-cn/README.md) - 中文课程与 assignments。
- [ShouZhengAI/CS146S_CN 研究分析](shouzhengai-cs146s-cn/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [ShouZhengAI/CS146S_CN 深度研究](shouzhengai-cs146s-cn/deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [ai-for-developers/awesome-vibe-coding 研究域](ai-for-developers-awesome-vibe-coding/README.md) - 精选 Vibe Coding 资料清单。
- [ai-for-developers/awesome-vibe-coding 研究分析](ai-for-developers-awesome-vibe-coding/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [ai-for-developers/awesome-vibe-coding 深度研究](ai-for-developers-awesome-vibe-coding/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [Daotin/ai-coding 研究域](daotin-ai-coding/README.md) - AI Coding 经验汇总。
- [Daotin/ai-coding 研究分析](daotin-ai-coding/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [Daotin/ai-coding 深度研究](daotin-ai-coding/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [earyantLe/vibe-coding-skill 研究域](earyantle-vibe-coding-skill/README.md) - Vibe Coding Skill / SOP 化。
- [earyantLe/vibe-coding-skill 研究分析](earyantle-vibe-coding-skill/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [earyantLe/vibe-coding-skill 深度研究](earyantle-vibe-coding-skill/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [liyupi/ai-guide 研究域](liyupi-ai-guide/README.md) - AI 资源大全与产品实用路线。
- [liyupi/ai-guide 研究分析](liyupi-ai-guide/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [liyupi/ai-guide 深度研究](liyupi-ai-guide/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [RooCodeInc/Roo-Code 研究域](roocodeinc-roo-code/README.md) - 已归档多 Agent 编辑器工具；当前已归档，仅作参考。
- [RooCodeInc/Roo-Code 研究分析](roocodeinc-roo-code/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [RooCodeInc/Roo-Code 深度研究](roocodeinc-roo-code/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [wendy7756/vibe-coding-guide 研究域](wendy7756-vibe-coding-guide/README.md) - 非程序员自然语言编程指南。
- [wendy7756/vibe-coding-guide 研究分析](wendy7756-vibe-coding-guide/analysis.md) - 结构化研究结论、可借鉴点、风险和下一轮任务。
- [wendy7756/vibe-coding-guide 深度研究](wendy7756-vibe-coding-guide/deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
</details>
## 使用方式
- 评估新技术、优秀 repo 或工程范式时，先写 research。
- 新增长期研究对象前，先按研究域治理契约判断它是否应该成为独立研究域，并用 `scripts/fetch-research-raw.py` 拉取原始材料。
- 外部仓库默认一仓库一研究域；横向比较只能放在索引或单独对比文档中。
- 对象会持续演化时，优先放入独立对象目录。
- 确认成熟后，再迁入更稳定的概念、参考或技能文档。
## 正文
正文已拆分到上方独立文档；本 README 只保留索引、旧锚点兼容入口和阅读顺序。
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# ai-for-developers/awesome-vibe-coding 研究域 Agent 指南
本目录维护 `ai-for-developers/awesome-vibe-coding` 的独立研究域。
## 目录职责
```text
ai-for-developers-awesome-vibe-coding/
├── README.md # 研究域入口和判断层
├── AGENTS.md # 本目录维护规则
├── domain.yml # 事实摘要层：仓库元数据、研究角色、来源证据
├── deep-dive.md # L2 结构深度研究、关键机制、迁移边界和验证任务
└── raw/ # 原始事实层：拉取到本地的一手材料快照
```
## 维护规则
- 本目录只研究 `ai-for-developers/awesome-vibe-coding`，不要混入其他仓库的横向比较正文。
- 动态事实必须写入 `domain.yml.github_observed`，并更新 `observed_at`。
- `raw/` 保存原始事实层，必须通过 `python3 scripts/fetch-research-raw.py` 刷新。
- 不手工改写 `raw/*.raw.*` 文件；稳定事实摘要再同步到 `domain.yml`。
- README 只写判断、定位、使用方式和后续观察点，不堆外部 README 全文。
- 如果需要横向比较，在 `docs/research/README.md` 或新的对比文档中处理，不把本目录重新变成聚合域。
- 修改后运行 `make sync-doc-toc` 和 `make test`。
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# ai-for-developers/awesome-vibe-coding 研究域
## 字多不看
- 本目录研究 `ai-for-developers/awesome-vibe-coding` 这个外部仓库。
- 当前优先级：P3；研究角色：精选 Vibe Coding 资料清单。
- GitHub 动态事实放在 `domain.yml`，观测日期为 2026-07-03。
## 快速导航
| 文档 | 定位 |
|:---|:---|
| [domain.yml](domain.yml) | 仓库事实快照、研究方向、优先级和来源证据。 |
| [analysis.md](analysis.md) | 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。 |
| [deep-dive.md](deep-dive.md) | L2 结构深度研究、关键机制、迁移边界和验证任务。 |
| [AGENTS.md](AGENTS.md) | 本研究域维护规则。 |
<details>
<summary><strong>完整细粒度目录（点击展开/收起）</strong></summary>
### 细粒度目录
- [domain.yml](domain.yml) - 仓库事实快照、研究方向、优先级和来源证据。
- [analysis.md](analysis.md) - 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。
- [deep-dive.md](deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [AGENTS.md](AGENTS.md) - 本研究域维护规则。
</details>
## 使用方式
- 先读本 README 的判断，再读 `analysis.md` 的结构化研究结论，再读 `deep-dive.md` 的 L2 证据，
最后读 `domain.yml` 的事实字段。
- 需要引用 stars、forks、release、归档状态时，先重新核验 GitHub。
- 如果形成稳定方法论，再迁入 concepts、references、workflow 或 skills。
## 正文
### 研究定位
`ai-for-developers/awesome-vibe-coding` 的当前研究定位是：精选 Vibe Coding 资料清单。
### 当前判断
适合作为 awesome-vibe-coding 的补充索引。
### 观察字段
- GitHub URL：https://github.com/ai-for-developers/awesome-vibe-coding
- 当前研究方向：`ecosystem-index`
- 当前优先级：P3
- 当前归档状态：`false`
- 主要语言：`None`
### 后续观察
- 是否有稳定文档结构、命令入口和可复用工作流。
- 是否能反哺本仓库的 concepts、references、workflow 或 skills。
- 是否存在许可证、归档状态、维护活跃度或生态迁移风险。
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# ai-for-developers/awesome-vibe-coding 研究分析
## 本轮结论
`ai-for-developers/awesome-vibe-coding` 的核心价值不是深度判断，而是轻量资源雷达。它用一个
README 把 Web builder、IDE、移动工具、插件、本地应用和 CLI 工具粗分出来，适合帮助本仓发现
候选资源和补分类词表。
本仓不能直接复制它的条目，因为它缺少结构化字段、状态、许可证、最后检查时间和采用风险。正确用法是：
把它作为 `assets/external-resources/` 的候选输入源，经过二次筛选后再进入本地资源注册表。
## 本地证据
- 研究对象：`ai-for-developers/awesome-vibe-coding`
- 当前研究角色：精选 Vibe Coding 资料清单
- 原始仓库：`raw/repository/`
- 原始来源清单：`raw/sources.yml`
- 事实摘要：`domain.yml`
## 对标拆解
| 项 | 内容 |
|:---|:---|
| 参考对象 | `ai-for-developers/awesome-vibe-coding` |
| 它解决的核心问题 | 快速发现 Vibe Coding 工具生态中的候选对象 |
| 核心机制 | 单 README 分类索引，按工具形态组织入口 |
| 真正带来结果的动作 | 用低成本分类让读者知道生态里有哪些工具族 |
| 可迁移做法 | 补充本仓资源分类、发现候选工具、观察工具族变化 |
| 不可迁移条件 | 不直接复制条目，不把 awesome list 当推荐结论 |
| 下一步试用动作 | 抽取分类词，与 `assets/external-resources/categories.yml` 做对照 |
## 改良迭代
| 改良目标 | 原模式 | 本仓版本 | 验证指标 |
|:---|:---|:---|:---|
| 资源发现 | README 手工分类 | 候选资源进入本地注册表前先二次筛选 | 新资源有 category、source、status、last_checked |
| 分类补齐 | Web / IDE / CLI 等工具族 | 本仓资源 category 增加缺失工具族 | 分类能覆盖 Web builder、IDE agent、CLI、plugin、local app |
| 候选升级 | 条目停留在列表 | 高价值条目升级为独立研究域 | 进入 P1/P2 候选必须有采用理由和风险 |
## 可迁移清单
- 使用它补全 Vibe Coding 工具族分类。
- 将条目作为资源候选，不作为最终推荐。
- 对重复出现的工具族提取关键词，反馈到关键词系统。
- 对高频出现的 coding agent、IDE agent、CLI 工具建立 P1/P2 研究候选。
## 不可迁移清单
- 不复制整张 awesome list。
- 不把没有许可证、维护状态和风险说明的条目放进推荐区。
- 不把它当作学习路径或工程规范。
## 验证动作
| 动作 | 成功信号 | 失败信号 |
|:---|:---|:---|
| 抽取分类词并对照本仓资源分类 | 发现缺失分类并能补齐 | 分类无变化，只多一批链接 |
| 抽样 20 条资源做二次筛选 | 每条有采用/不采用理由 | 仍然只是链接搬运 |
| 挑出 3 个高价值工具进入候选研究 | 能说明为什么值得深挖 | 候选没有优先级和风险 |
## 沉淀判断
- 稳定结果进入 `assets/external-resources/` 和 `metadata/taxonomy.yml`。
- 本研究域保持 P3 低频雷达，不升级为方法论主线。
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# ai-for-developers/awesome-vibe-coding 深度研究
## 研究级别
- 当前级别：L2 结构深度研究。
- 研究对象：`ai-for-developers/awesome-vibe-coding`。
- 证据来源：本目录 `raw/` 下的 GitHub 元数据、README 快照和本地仓库工作树。
- 观察日期：2026-07-03。
## L2 结论
`ai-for-developers/awesome-vibe-coding` 的核心价值不是方法论，而是轻量生态雷达。它用单个
README 把 Vibe Coding 相关工具、文章、项目文档、CLI、IDE、插件、监控和任务管理入口压成一张
候选清单，适合发现资源缺口和观察生态分类。
对本仓最重要的启发是：awesome list 只能作为候选入口，不能直接成为推荐结论。资源一旦进入
本仓，需要经过分类、去重、许可证、维护状态、最后检查时间和采用理由等治理字段。
## 本地证据
- `raw/repository/readme.md`：主清单入口，按工具形态组织资源。
- `raw/github-root-contents.raw.json`：仓库根目录事实，显示该项目主要由单一 README 承载。
- `raw/github-languages.raw.json`：语言统计为空，说明它不是代码产品或课程仓库。
- `raw/sources.yml`：`license` 和 `latest-release` 抓取均为缺失或错误，说明采用前必须二次核验。
- `domain.yml`：当前优先级为 P3，研究方向为 `ecosystem-index`。
## 关键机制
### 低摩擦收集入口
单 README 清单降低了贡献和阅读门槛。它适合快速收集候选工具，但也意味着事实字段、验证状态和
生命周期管理都很弱。
### 按工具形态分类
README 将资源分散到 Web builder、IDE、mobile tool、extension、desktop/local app、CLI tool、
task management、monitoring、documentation 和 article 等类别。这个分类方式能帮助本仓检查
资源库是否缺少某类入口。
### 生态雷达而非采用证据
项目本身没有测试、脚本、schema、资源状态字段或许可证治理。它可以告诉我们“有哪些候选对象”，
但不能告诉我们“哪些对象应该被本仓推荐”。
## 可迁移模式
- 用轻量清单发现本仓资源分类缺口。
- 把 Web、IDE、CLI、插件、桌面、本地、监控、文档和文章作为资源候选维度。
- 将每个候选资源先进入 `assets/external-resources/` 或研究域，而不是直接进入稳定教程。
- 为 awesome list 类资源设置低优先级观察状态，只有被验证后才升级到 P1/P2。
- 对缺少许可证、release、维护状态的资源建立默认风险标记。
## 对本仓的影响
本仓不应该把该项目内容照搬到资源页，而应该把它作为资源治理的输入：
- 对照本仓资源表，检查是否缺少 IDE、CLI、插件、监控、任务管理和项目文档类资源。
- 把候选资源转换为结构化字段：名称、类别、来源、许可证、状态、最后检查时间和采用理由。
- 将高价值候选对象单独拆成研究域，避免继续做大杂烩索引。
- 在 `research-transfer-synthesis.md` 中保留它的定位：轻量工具分类雷达。
## 风险和待验证项
- 缺少许可证信息，不能直接复制内容或列表结构作为本仓稳定资产。
- 单 README 清单容易过期，必须以本仓刷新日期和二次核验为准。
- 该项目没有工程闭环，不能支撑 scripts、workflow 或 skills 的设计结论。
- stars 和更新时间属于动态事实，后续引用前必须重新核验 GitHub。
## 下一步 L3 验证任务
- 抽取 20 个候选资源进入本仓资源候选表，补齐类别、许可证、状态和最后检查时间。
- 对照本仓资源库，找出当前缺失的工具形态分类。
- 为 awesome list 类来源增加 `radar_only` 或等价状态，防止被误读为正式推荐。
- 将被多源交叉验证的候选对象升级为独立研究域，而不是继续堆在资源清单里。
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version: 1
repo:
name: ai-for-developers/awesome-vibe-coding
source_name: ai-for-developers/awesome-vibe-coding
url: https://github.com/ai-for-developers/awesome-vibe-coding
research:
domain_id: ai-for-developers-awesome-vibe-coding
domain_name: ai-for-developers/awesome-vibe-coding 研究域
primary_direction: ecosystem-index
role: 精选 Vibe Coding 资料清单
priority: 3
why_study: 适合作为 awesome-vibe-coding 的补充索引。
github_observed:
observed_at: '2026-07-03'
source: gh repo view
stars: 767
forks: 166
archived: false
language: null
license: null
default_branch: main
pushed_at: '2026-04-18T13:36:43Z'
updated_at: '2026-07-02T14:24:51Z'
latest_release: null
homepage: ''
topics:
- ai
- ai-app-builder
- ai-ide
- vibe
- vibe-coding
- vibecoding
- awesome-vibe-coding
- ai-agents
- ai-tools
- awesome-ai
- awesome-ai-tools
- awesome-list
- vibecode
- vibecoding-tool
source_evidence:
file: ChatGPT-中文Vibe Coding仓库 (2).md
line: 50
maintenance:
fact_policy: GitHub 动态字段只代表 observed_at 当日快照，更新结论前必须重新核验。
split_policy: 本目录已经是一等研究域；更深分析放入本目录新增文档。
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# raw/ Agent 指南
本目录是 `ai-for-developers/awesome-vibe-coding` 的原始事实层。
## 维护规则
- 只保存从研究对象拉取的一手材料，不写分析判断。
- `repository/` 是本地 Git 工作树，刷新时由脚本 clone 或 fast-forward pull。
- 不手工改写 `*.raw.*` 文件内容；需要刷新时运行 `python3 scripts/fetch-research-raw.py`。
- `sources.yml` 必须记录拉取时间、来源命令和每个文件的状态。
- 外部 README 原文必须保存为 `.txt`，避免本仓库 Markdown 链接检查误判。
- 分析、判断、采用建议和沉淀路径写回上一级 `README.md`、`analysis.md` 或 `decisions.md`。
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# raw 事实层
本目录保存 `ai-for-developers/awesome-vibe-coding` 的本地原始材料快照。
这里不写分析结论，只保存可复查的一手资料：
- `sources.yml`：来源清单、拉取时间、命令和文件状态。
- `repository/`：Git 仓库工作树；本目录由 `.gitignore` 忽略，只作为本地研究材料。
- `github-repo.raw.json`：GitHub 仓库元数据。
- `github-readme.raw.md.txt`：GitHub README 原文快照。
- `github-license.raw.txt`：GitHub license 原文快照；仓库无 license 时可能不存在。
- `github-root-contents.raw.json`：默认分支根目录内容快照。
- `github-languages.raw.json`：GitHub language 统计快照。
- `github-latest-release.raw.json`：最新 release 快照；无 release 时可能不存在。
`repository/` 是外部源码快照，不参与本仓库 Markdown、链接、README/AGENTS 覆盖检查。原始 README 使用 `.txt` 后缀保存，避免其中的外部相对链接被本仓库 Markdown 链接检查误判。
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{}
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# Awesome Vibe Coding [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)
> A hand-picked collection of tools and references for building software with the help of AI—through prompts, iterations, and exploration.
## Overview
This list focuses on tools and workflows where AI plays a central role in the development process. Instead of traditional coding, this approach emphasizes describing ideas, iterating quickly, and trusting the process—even when you’re not sure where it’s headed.
*You can find a searchable, more detailed list on [AI For Developers](https://aifordevelopers.org)*
----
**Reach thousands of developers building with AI by sponsoring this list, our [newsletter](https://aifordevelopers.substack.com/) and [AI For Developers](https://aifordevelopers.org/). Contact us at [aifordevelopers.org/advertise](https://aifordevelopers.org/advertise)**
----
## Table of Contents
* [What is](#what-is)
* [Web-Based Builders](#web-based-builders)
* [Editors and IDEs](#editors-and-ides)
* [Mobile Tools](#mobile-tools)
* [Extensions & Plugins](#extensions--plugins)
* [Desktop & Local Apps](#desktop--local-apps)
* [CLI Tools](#cli-tools)
* [AI-Driven Task Management](#ai-driven-task-management)
* [Monitoring & Cost Tracking](#monitoring--cost-tracking)
* [Project Documentation](#project-documentation)
* [Articles & Updates](#articles--updates)
* [Contributing](#contributing)
---
## What is
* [Karpathy on the "vibe coding" mindset](https://x.com/karpathy/status/1886192184808149383) — Not traditional coding. More like shaping software through language and intuition.
* [AI Coding Guide by Automata](https://github.com/automata/aicodeguide) — A structured starting point for newcomers using AI-first development approaches.
---
## Web-Based Builders
* [Bolt.new](https://bolt.new/) — Rapidly prototype and launch web and mobile apps by prompting.
* [Lovable](https://lovable.dev/) — Full-stack applications from simple ideas.
* [Vercel’s v0](https://v0.dev/chat) — Helps design and implement UIs from natural language.
* [Capacity](https://capacity.so/) — Create production-ready web apps in minutes.
* [CHAI.new](https://chai.new) — Code and deploy AI agents with prompts.
* [Replit](https://replit.com/) — Type what you want and let the AI construct it.
* [Create](https://www.create.xyz/) — Converts text prompts into usable tools or websites.
* [Trickle](https://www.trickle.so/) — AI-based visual builder for websites and apps.
* [Tempo](https://www.tempo.new/) — Build React projects much faster through AI assistance.
* [Softgen](https://softgen.ai/) — Describe a concept and generate a working full-stack app.
* [Lazy AI](https://getlazy.ai/) — Enterprise-focused prompt-based application builder.
* [HeyBoss](https://www.heyboss.xyz/) — Generate functional websites quickly.
* [Creatr](https://getcreatr.com/) — Build landing pages and simple apps instantly.
* [Rork](https://rork.app/) — A tool focused on generating mobile apps.
* [Firebase Studio](https://studio.firebase.google.com/) — Google's take on agent-driven full-stack development.
* [Napkins](https://www.napkins.dev/) — Converts mockups or screenshots into working code.
* [HeroUI Chat](https://heroui.chat/) — Build interfaces without design expertise.
* [Rocket.new](https://www.rocket.new/) — Low-code experience for shipping apps.
* [embedible.io](https://embedible.io/) - AI that transforms your electronics ideas into working projects.
* [FlyPloy](https://flyploy.com/en) — A modern application deployment platform that simplifies global delivery with one-click deploys, Docker, and Kubernetes support. Ideal for launching AI-assisted applications in seconds.
* [MyVibe](https://myvibe.so/) — Instant deployment for AI-generated web apps. Publish via Claude Code skills or direct upload.
* [Rosebud AI](https://rosebud.ai) — Vibe coding platform for creating 3D games and interactive web apps with AI.
* [Forge](https://forge-web.rebaselabs.online/) — AI-powered full-stack app creator with BYOK (bring your own API key). Multi-stage pipeline: planning, architecture, code generation, and verification.
---
## Editors and IDEs
* [Windsurf](https://codeium.com/windsurf) — AI-focused development environment by Codeium.
* [Cursor](https://www.cursor.com/) — One of the most advanced AI-first code editors.
* [Zed](https://zed.dev/) — Built for real-time team collaboration with AI assistance.
* [Amazon Kiro](https://kiro.dev) — An AI-powered IDE from prototype to production.
---
## Mobile Tools
* [VibeCode](https://www.vibecodeapp.com/) — A mobile-first app creator powered by AI.
* [IM.codes](https://github.com/im4codes/imcodes) — Mobile/web control layer for Claude Code, Codex, Gemini CLI, and other terminal-based coding agents.
---
## Extensions & Plugins
* [Cline](https://cline.bot/) — Connects to your CLI and editor, interprets natural commands.
* [Roo Code](https://github.com/RooVetGit/Roo-Code) — An enhanced version of Cline.
* [avante.nvim](https://github.com/yetone/avante.nvim) — Neovim integration modeled after Cursor’s AI features.
* [Prompt Tower](https://github.com/backnotprop/prompt-tower) — A prompt creation interface supporting complex code blocks.
* [Augment Code](https://www.augmentcode.com/) — Tailored for navigating and working with large repositories.
* [Continue](https://github.com/continuedev/continue) — Build your own in-editor AI agents using plugins and rules.
* [GitHub Copilot](https://github.com/features/copilot) — Integrated assistant offering code suggestions, chats, and context-aware actions.
* [Amazon Q](https://aws.amazon.com/q/developer) — AWS’s generative AI solution for developers.
* [Superdesign](https://www.superdesign.dev/) — AI design agent for fast UI iterations.
* [toprank](https://github.com/nowork-studio/toprank) — Open-source Claude Code plugin with 9 SEO and Google Ads skills. Connects Google Search Console, PageSpeed Insights, and Google Ads API; ships meta tag and schema markup fixes to WordPress/Strapi/Contentful/Ghost. MIT, 107⭐.
* [dbForge AI Assistant](https://www.devart.com/dbforge/ai-assistant/) - Integrated AI tool that generates, optimizes, explains, and fixes SQL queries.
* [Frontman](https://github.com/frontman-ai/frontman) — Open-source AI agent that lives in your browser — click any element, describe changes in plain English, and get real code edits with hot reload. Works with Next.js, Vite, and Astro.
* [Mysti](https://github.com/DeepMyst/Mysti) - Multi-agent AI coding assistant for VS Code with brainstorm mode. Supports Claude Code, Codex, Gemini, Cline, and GitHub Copilot.
* [AgentLint](https://github.com/0xmariowu/AgentLint) — 33 evidence-backed checks for AI-friendly repos — file structure, instruction quality, build setup, session continuity, security posture. Claude Code plugin.
---
## Desktop & Local Apps
* [Dyad](https://www.dyad.sh/) — A lightweight, local platform for creating AI-driven apps without depending on the cloud.
* [ClaudeCode Launchpad CLI](https://github.com/noambrand/kivun-terminal) — Windows & macOS installer and launcher for Claude Code. 2-minute setup: auto-installs Node.js, Git & Claude Code; adds a live two-line status bar (model, context %, usage limits), desktop shortcut with folder picker, and right-click "Open with ClaudeCode Launchpad CLI" context menu on Windows folders.
---
## CLI Tools
* [claude-code](https://github.com/anthropics/claude-code) — Works across codebases, provides explanations, automates tasks.
* [memov](https://github.com/memovai/memov) — Git-based, traceable memory layer for Claude Code.
* [aider](https://aider.chat/) — Code side-by-side with AI from your terminal.
* [Goose](https://block.github.io/goose/) — Local agent framework compatible with multiple models.
* [MyCoder.ai](https://github.com/drivecore/mycoder) — Modular agent with GitHub integration.
* [RA.Aid](https://github.com/ai-christianson/RA.Aid) — Task-based AI built with LangGraph.
* [CodeSelect](https://github.com/maynetee/codeselect) — Sends structured source context to LLMs.
* [OpenAI Codex CLI](https://github.com/openai/codex) — Experimental terminal assistant.
* [Gemini CLI](https://github.com/google-gemini/gemini-cli) — Terminal assistant built around Google Gemini.
* [ReviewCerberus](https://github.com/Kirill89/reviewcerberus) - Open-source AI code review tool for analyzing git branch differences with comprehensive security, performance, and quality analysis.
* [OpenPaw](https://github.com/daxaur/openpaw) — Turns Claude Code into a personal assistant with 38 skills for email, calendar, Spotify, smart home, and more.
* [Autohand Code CLI](https://github.com/autohandai/code-cli) — Self-evolving autonomous coding agent for the terminal with 40+ tools, multi-LLM support, and a modular skills system.
* [Bernstein](https://github.com/chernistry/bernstein) — Deterministic orchestrator for vibe coding at scale. Spawns parallel AI coding agents from a single goal, verifies with tests, auto-commits.
* [sober-coding](https://github.com/voidborne-d/sober-coding) — Vibe code quality analyzer. 27 checks across security, architecture, duplication, error handling, dependencies, testing, and dead code. Language-agnostic with fix suggestions and CI mode.
* [VibeGrid](https://github.com/jcanizalez/vibegrid) — Multi-agent terminal manager with task queues, workflow automation, and inline diff review.
---
## AI-Driven Task Management
* [Boomerang Tasks](https://docs.roocode.com/features/boomerang-tasks) — Automatically turns big ideas into task queues.
* [Claude Task Master](https://github.com/eyaltoledano/claude-task-master) — Compatible with popular AI IDEs, breaks down work into subtasks.
* [agent-hub](https://github.com/Dominic789654/agent-hub) — Local-first multitask board for routing, sequencing, and observing repo-local coding agents across projects.
---
## Monitoring & Cost Tracking
* [Budi](https://github.com/siropkin/budi) — Local-first cost analytics for AI coding agents. Tracks token usage and spend across Claude Code and Cursor.
---
## Project Documentation
* [CodeGuide](https://www.codeguide.dev/) — Tool that builds documentation for AI-built projects.
* [LynxPrompt](https://github.com/GeiserX/LynxPrompt) — Self-hostable AI config management platform for teams. Manages AGENTS.md, CLAUDE.md, .cursor/rules/, slash commands, and 30+ formats.
* [Claude Code Mastery](https://github.com/ShipWithAI/claude-code-mastery) — Structured course for mastering Claude Code workflows, including security, automation, and multi-agent patterns.
---
## Articles & Updates
* [Prompt Engineering for Developers](https://addyo.substack.com/p/the-prompt-engineering-playbook-for)
* [What Vibe Coding Actually Means](https://theconversation.com/what-is-vibe-coding-a-computer-scientist-explains-what-it-means-to-have-ai-write-computer-code-and-what-risks-that-can-entail-257172)
* [LLM Pair Programming](https://pmbanugo.me/blog/peer-programming-with-llms)
* [The Way of Code](https://www.thewayofcode.com/)
* [2025 Tooling Overview on LinkedIn](https://www.linkedin.com/pulse/state-vibe-coding-tools-may-2025-nufar-gaspar-x1znf)
* [Karpathy on Menus and Vibes](https://karpathy.bearblog.dev/vibe-coding-menugen/)
* [Fireship: Mindset Video](https://www.youtube.com/watch?v=Tw18-4U7mts)
* [Ars Technica on AI Development Futures](https://arstechnica.com/ai/2025/03/is-vibe-coding-with-ai-gnarly-or-reckless-maybe-some-of-both/)
* [The New Stack – Everyone Can Program](https://thenewstack.io/vibe-coding-where-everyone-can-speak-computer-programming/)
* [NYTimes: Personal Vibe Coding Experience](https://www.nytimes.com/2025/02/27/technology/personaltech/vibecoding-ai-software-programming.html)
* [CodingButVibes – What Is Vibe Coding](https://www.codingbutvibes.com/what-is-vibe-coding) — Practical breakdown of the vibe coding approach, with tool comparisons and real developer workflows.
* [Reddit: /r/vibecoding](https://www.reddit.com/r/vibecoding/)
* [Reddit: /r/ChatGPTCoding](https://www.reddit.com/r/ChatGPTCoding/)
* [Vibe Engineering](https://www.manning.com/books/vibe-engineering)
---
## Contributing
Found something interesting or built your own tool? Contributions are encouraged—see the [contribution guide](CONTRIBUTING.md) for details.
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{
"createdAt": "2023-08-28T16:37:06Z",
"defaultBranchRef": {
"name": "main"
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"primaryLanguage": null,
"pushedAt": "2026-04-18T13:36:43Z",
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{
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{
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{
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[
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"html_url": "https://github.com/ai-for-developers/awesome-vibe-coding/blob/main/readme.md",
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version: 1
domain_id: ai-for-developers-awesome-vibe-coding
object:
type: github_repository
name: ai-for-developers/awesome-vibe-coding
url: https://github.com/ai-for-developers/awesome-vibe-coding
pulled_at: '2026-07-02T22:47:14+00:00'
puller: scripts/fetch-research-raw.py
files:
- path: repository/
kind: git-working-tree
status: ok
source: 'git clone --depth=1 --single-branch --no-tags https://github.com/ai-for-developers/awesome-vibe-coding.git docs/research/ai-for-developers-awesome-vibe-coding/raw/repository'
- path: github-repo.raw.json
kind: repository-metadata
status: ok
source: 'gh repo view ai-for-developers/awesome-vibe-coding --json nameWithOwner,url,description,homepageUrl,isArchived,isFork,isMirror,defaultBranchRef,licenseInfo,primaryLanguage,repositoryTopics,stargazerCount,forkCount,watchers,createdAt,updatedAt,pushedAt,latestRelease --jq .'
- path: github-readme.raw.md.txt
kind: readme
status: ok
source: 'gh api repos/ai-for-developers/awesome-vibe-coding/readme -H Accept: application/vnd.github.raw'
- path: github-license.raw.txt
kind: license
status: missing_or_error
source: 'gh api repos/ai-for-developers/awesome-vibe-coding/license -H Accept: application/vnd.github.raw'
message: 'gh: Not Found (HTTP 404)'
- path: github-root-contents.raw.json
kind: root-contents
status: ok
source: 'gh api repos/ai-for-developers/awesome-vibe-coding/contents'
- path: github-languages.raw.json
kind: languages
status: ok
source: 'gh api repos/ai-for-developers/awesome-vibe-coding/languages'
- path: github-latest-release.raw.json
kind: latest-release
status: missing_or_error
source: 'gh api repos/ai-for-developers/awesome-vibe-coding/releases/latest'
message: 'gh: Not Found (HTTP 404)'
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# Aider-AI/aider 研究域 Agent 指南
本目录维护 `Aider-AI/aider` 的独立研究域。
## 目录职责
```text
aider-ai-aider/
├── README.md # 研究域入口和判断层
├── AGENTS.md # 本目录维护规则
├── domain.yml # 事实摘要层：仓库元数据、研究角色、来源证据
├── analysis.md # L1 结构化研究结论、可借鉴点、风险和下一轮任务
├── deep-dive.md # L2 源码/结构深度研究、关键机制和可迁移模式
└── raw/ # 原始事实层：拉取到本地的一手材料快照
```
## 维护规则
- 本目录只研究 `Aider-AI/aider`，不要混入其他仓库的横向比较正文。
- 动态事实必须写入 `domain.yml.github_observed`，并更新 `observed_at`。
- `raw/` 保存原始事实层，必须通过 `python3 scripts/fetch-research-raw.py` 刷新。
- 不手工改写 `raw/*.raw.*` 文件；稳定事实摘要再同步到 `domain.yml`。
- README 只写判断、定位、使用方式和后续观察点，不堆外部 README 全文。
- `analysis.md` 写 L1 结构化理解；`deep-dive.md` 写 L2 源码证据、关键机制和可迁移模式。
- 如果需要横向比较，在 `docs/research/README.md` 或新的对比文档中处理，不把本目录重新变成聚合域。
- 修改后运行 `make sync-doc-toc` 和 `make test`。
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# Aider-AI/aider 研究域
## 字多不看
- 本目录研究 `Aider-AI/aider` 这个外部仓库。
- 当前优先级：P1；研究角色：终端 AI 结对编程工具。
- GitHub 动态事实放在 `domain.yml`，观测日期为 2026-07-03。
## 快速导航
| 文档 | 定位 |
|:---|:---|
| [domain.yml](domain.yml) | 仓库事实快照、研究方向、优先级和来源证据。 |
| [analysis.md](analysis.md) | 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。 |
| [deep-dive.md](deep-dive.md) | L2 源码/结构深度研究、关键机制和可迁移模式。 |
| [AGENTS.md](AGENTS.md) | 本研究域维护规则。 |
<details>
<summary><strong>完整细粒度目录（点击展开/收起）</strong></summary>
### 细粒度目录
- [domain.yml](domain.yml) - 仓库事实快照、研究方向、优先级和来源证据。
- [analysis.md](analysis.md) - 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。
- [deep-dive.md](deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [AGENTS.md](AGENTS.md) - 本研究域维护规则。
</details>
## 使用方式
- 先读本 README 的判断，再读 `analysis.md` 和 `deep-dive.md` 的研究结论，最后读 `domain.yml`。
- 需要引用 stars、forks、release、归档状态时，先重新核验 GitHub。
- 如果形成稳定方法论，再迁入 concepts、references、workflow 或 skills。
## 正文
### 研究定位
`Aider-AI/aider` 的当前研究定位是：终端 AI 结对编程工具。
### 当前判断
适合研究 Git 友好、模型无关、终端工作流和真实 repo 修改。
### 观察字段
- GitHub URL：https://github.com/Aider-AI/aider
- 当前研究方向：`coding-agent-tooling`
- 当前优先级：P1
- 当前归档状态：`false`
- 主要语言：`Python`
### 后续观察
- 是否有稳定文档结构、命令入口和可复用工作流。
- 是否能反哺本仓库的 concepts、references、workflow 或 skills。
- 是否存在许可证、归档状态、维护活跃度或生态迁移风险。
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# Aider-AI/aider 研究分析
## 本轮结论
`Aider-AI/aider` 的核心价值不是终端聊天，而是 Git 驱动的 AI 编辑闭环。它把仓库状态、编辑格式、
repo map、命令执行、lint/test 和提交协作放进同一条循环，让 AI 修改始终能被 diff、验证、回滚和审查。
本仓最应该迁移的是“AI 修改必须进入证据链”：任何文档、研究、脚本或资源变更，都要能说明 diff 范围、
验证命令、失败修复和提交边界。
## 本地证据
- 研究对象：`Aider-AI/aider`
- 当前研究角色：终端 AI 结对编程工具
- 原始仓库：`raw/repository/`
- 原始来源清单：`raw/sources.yml`
- 事实摘要：`domain.yml`
- 深度证据：`deep-dive.md`
## 对标拆解
| 项 | 内容 |
|:---|:---|
| 参考对象 | `Aider-AI/aider` |
| 它解决的核心问题 | 让 AI 对真实仓库的修改可 diff、可测试、可提交、可回滚 |
| 核心机制 | `repo.py` 管 Git 状态，`repomap.py` 压缩上下文，`coders/` 定义编辑协议，`linter.py` 接入反馈 |
| 真正带来结果的动作 | 把 AI 输出变成 Git 工作流里的可审查补丁，而不是孤立文本 |
| 可迁移做法 | dirty state 检查、diff 审查、门禁命令、验证证据和提交叙事 |
| 不可迁移条件 | 不复制完整终端产品、多模型配置和 Python 编辑器实现 |
| 下一步试用动作 | 在 `docs/workflow/` 沉淀“AI 修改 -> diff 审查 -> make test -> commit”闭环 |
## 改良迭代
| 改良目标 | 原模式 | 本仓版本 | 验证指标 |
|:---|:---|:---|:---|
| Git 状态护栏 | Aider 围绕 Git dirty state 和 commit 工作 | 每次任务先看 `git status`，不覆盖用户改动 | 变更说明能区分用户改动和本轮改动 |
| 文档上下文压缩 | Aider 用 repo map 选择上下文 | 本仓建立 research/docs 入口地图和索引校验 | 新文档不会漏进 README、metadata、llms |
| 反馈循环 | Aider 把 lint/test 反馈接进对话 | 本仓统一用 `make test` 做文档门禁 | 修改后失败项能回到具体文件修复 |
## 可迁移清单
- 把“修改前检查工作区状态”写成所有 AI 工程任务默认动作。
- 把 `make test`、`git diff --check` 和关键脚本输出纳入交付说明。
- 为研究域建立文档地图或索引生成机制，减少长文档漂移。
- 对大文件修改优先使用局部 patch，避免全文件重写带来无关 diff。
## 不可迁移清单
- 不把本仓变成 Aider 竞品。
- 不复制其多模型兼容层、coder 实现和交互式命令系统。
- 不把 repo map 当成万能方案；本仓优先解决 Markdown 索引漂移和研究域路由。
## 验证动作
| 动作 | 成功信号 | 失败信号 |
|:---|:---|:---|
| 为一次文档任务记录状态、diff、门禁和提交说明 | 后续审查能复现变更链路 | 只能从对话里猜为什么这么改 |
| 抽样新增文档后跑索引检查 | README、metadata、llms 同步 | 新文档存在但入口缺失 |
| 对同一类研究文档使用固定分析骨架 | 读者能横向比较对象 | 每篇分析结构不同、不可比较 |
## 沉淀判断
- 稳定结论应下沉到 `docs/workflow/` 的 AI 修改闭环。
- `deep-dive.md` 保留源码证据；本文件负责把证据转成迁移动作。
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# Aider-AI/aider 深度研究
## 研究级别
- 当前级别：L2 源码/结构深度研究。
- 研究对象：`Aider-AI/aider`。
- 证据来源：本目录 `raw/` 下的 GitHub 元数据、README 快照和本地仓库工作树。
- 观察日期：2026-07-03。
## L2 结论
`Aider-AI/aider` 的核心不是“聊天式写代码”，而是终端里的 Git 驱动编辑循环。它把仓库状态、
代码上下文、编辑格式、命令执行、lint/test、模型配置和用户交互拆成独立模块，让 agent 的每次
修改都尽量落在可 diff、可回滚、可验证的 Git 工作流中。
对本仓最重要的启发是：AI 编码工具的质量边界，主要由编辑协议、仓库上下文选择、验证门禁和
Git 状态管理决定，而不是由提示词长短决定。
## 源码证据
- `raw/repository/aider/main.py`：CLI 主入口，负责把参数、模型、仓库和交互流程组装起来。
- `raw/repository/aider/args.py`：参数层，说明用户可控配置是产品接口的一部分。
- `raw/repository/aider/repo.py`：Git 仓库状态层，承载 diff、commit、dirty state 等行为。
- `raw/repository/aider/repomap.py`：仓库地图层，负责从代码库中压缩可用上下文。
- `raw/repository/aider/commands.py`：命令系统，承载终端内的人机交互入口。
- `raw/repository/aider/run_cmd.py`：本地命令执行层，连接 AI 建议和真实环境。
- `raw/repository/aider/linter.py`：lint 反馈层，把工具结果变成修复循环的一部分。
- `raw/repository/aider/models.py`：模型配置层，说明多模型支持需要独立治理。
- `raw/repository/aider/sendchat.py`：模型调用层，连接上下文、消息和模型响应。
- `raw/repository/aider/coders/base_coder.py`：coder 抽象基类，定义编辑策略共同边界。
- `raw/repository/aider/coders/architect_coder.py`：架构/规划型 coder。
- `raw/repository/aider/coders/editblock_coder.py`：基于 edit block 的局部编辑策略。
- `raw/repository/aider/coders/udiff_coder.py`：基于 unified diff 的编辑策略。
- `raw/repository/aider/coders/patch_coder.py`：基于 patch 的编辑策略。
- `raw/repository/tests/`：测试层，覆盖命令、仓库、lint、repo map 和核心工作流。
## 关键机制
### Git 是工作流中心
Aider 把 Git 状态放在核心位置。它不是让 AI 随意改文件，而是围绕当前仓库、diff、commit、
脏工作树和可回滚状态组织工作。这一点适合所有 coding agent：写代码只是动作，Git 才是
工程协作的事实边界。
### 编辑格式是产品接口
`coders/` 中存在多种 coder：whole file、edit block、unified diff、patch、architect 等。
这说明“AI 如何表达修改”不是实现细节，而是影响可靠性、可审查性和失败模式的产品接口。
### repo map 是上下文压缩层
`repomap.py` 体现了一个关键设计：大仓库不能简单把所有文件塞进上下文，必须有面向任务的结构化
摘要和检索策略。上下文质量决定修改质量，垃圾上下文会直接制造垃圾结果。
### lint/test 是反馈回路
`linter.py`、`run_cmd.py` 和测试目录说明 Aider 将工具反馈接入循环。成熟 agent 不只是生成补丁，
还要能读取失败、缩小范围、再次修复。
## 可迁移模式
- 将“编辑格式”视为正式协议：全文件、diff、patch、结构化 block 的适用边界要写清楚。
- 将 Git 状态作为 AI 修改的事实源：修改前检查 dirty state，修改后保留 diff 和验证证据。
- 为大文档/大仓库建立 repo map 或文档 map，而不是让 AI 盲读整个仓库。
- 把 lint、test、link check 和脚本校验结果作为修复循环输入。
- 对不同任务区分规划型、编辑型、审查型和问答型 agent 行为。
## 对本仓的影响
本仓现在已经有 Markdown 门禁、链接检查、raw 研究域和 AI 引用入口。Aider 的模式提醒我们：
- 文档修改也需要 Git 状态意识，避免把用户未提交修改误当作自己的改动。
- 大量 Markdown 文档需要“文档地图”，否则索引和引用会漂移。
- 研究域 L2/L3 产物应当可 diff、可审查、可回滚，而不是只在对话里口头总结。
- 提交前门禁应继续保持 `make test` 的统一入口。
## 风险和待验证项
- 本轮只做源码结构研究，没有运行 Aider 的测试套件或交互流程。
- Aider 的 Python 实现细节不应被本仓直接复制；本仓主要迁移工作流和治理边界。
- 不同编辑格式的真实成功率需要通过任务集 benchmark 验证，不能只靠结构判断。
## 下一步 L3 验证任务
- 为本仓建立“文档地图/研究地图”的生成或校验机制，降低长文档索引漂移。
- 把 Git dirty state、门禁命令和验证证据纳入研究域 closeout 模板。
- 在 `docs/workflow/` 沉淀“AI 修改 -> diff 审查 -> 门禁 -> 提交”的最小闭环。
- 对本仓常见 Markdown 修改任务设计小型 benchmark，比较全文件编辑和局部 patch 的稳定性。
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version: 1
repo:
name: Aider-AI/aider
source_name: aider-ai/aider
url: https://github.com/Aider-AI/aider
research:
domain_id: aider-ai-aider
domain_name: Aider-AI/aider 研究域
primary_direction: coding-agent-tooling
role: 终端 AI 结对编程工具
priority: 1
why_study: 适合研究 Git 友好、模型无关、终端工作流和真实 repo 修改。
github_observed:
observed_at: '2026-07-03'
source: gh repo view
stars: 46962
forks: 4680
archived: false
language: Python
license: apache-2.0
default_branch: main
pushed_at: '2026-05-22T14:02:20Z'
updated_at: '2026-07-02T21:52:05Z'
latest_release: v0.86.0
homepage: https://aider.chat/
topics:
- chatgpt
- cli
- command-line
- gpt-4
- openai
- gpt-3
- gpt-35-turbo
- claude-3
- gpt-4o
- anthropic
- gemini
- llama
- sonnet
source_evidence:
file: ChatGPT-中文Vibe Coding仓库 (2).md
line: 57
maintenance:
fact_policy: GitHub 动态字段只代表 observed_at 当日快照，更新结论前必须重新核验。
split_policy: 本目录已经是一等研究域；更深分析放入本目录新增文档。
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# raw/ Agent 指南
本目录是 `Aider-AI/aider` 的原始事实层。
## 维护规则
- 只保存从研究对象拉取的一手材料，不写分析判断。
- `repository/` 是本地 Git 工作树，刷新时由脚本 clone 或 fast-forward pull。
- 不手工改写 `*.raw.*` 文件内容；需要刷新时运行 `python3 scripts/fetch-research-raw.py`。
- `sources.yml` 必须记录拉取时间、来源命令和每个文件的状态。
- 外部 README 原文必须保存为 `.txt`，避免本仓库 Markdown 链接检查误判。
- 分析、判断、采用建议和沉淀路径写回上一级 `README.md`、`analysis.md` 或 `decisions.md`。
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# raw 事实层
本目录保存 `Aider-AI/aider` 的本地原始材料快照。
这里不写分析结论，只保存可复查的一手资料：
- `sources.yml`：来源清单、拉取时间、命令和文件状态。
- `repository/`：Git 仓库工作树；本目录由 `.gitignore` 忽略，只作为本地研究材料。
- `github-repo.raw.json`：GitHub 仓库元数据。
- `github-readme.raw.md.txt`：GitHub README 原文快照。
- `github-license.raw.txt`：GitHub license 原文快照；仓库无 license 时可能不存在。
- `github-root-contents.raw.json`：默认分支根目录内容快照。
- `github-languages.raw.json`：GitHub language 统计快照。
- `github-latest-release.raw.json`：最新 release 快照；无 release 时可能不存在。
`repository/` 是外部源码快照，不参与本仓库 Markdown、链接、README/AGENTS 覆盖检查。原始 README 使用 `.txt` 后缀保存，避免其中的外部相对链接被本仓库 Markdown 链接检查误判。
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"published_at": "2025-08-09T17:42:19Z",
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"body": "- Added support for all GPT-5 models.\r\n- Added support for Grok-4 via `xai/grok-4` and `openrouter/x-ai/grok-4` model names.\r\n- Added support for `gemini/gemini-2.5-flash-lite-preview-06-17` model, by Tamir Zahavi-Brunner.\r\n- `/clear` now prints “All chat history cleared.” so you know it worked, by Zexin Yuan.\r\n- `/undo` output now shows only the first line of each commit message, making it easier to read.\r\n- Added support for `openrouter/moonshotai/kimi-k2` model, by Jack Harrington.\r\n- Display model announcements with no-arg `/model` command.\r\n- Fixed an issue where new settings for an existing model didn't replace the old ones, by Andrew Grigorev.\r\n- Fixed analytics to support the latest PostHog SDK event-capture API.\r\n- Bumped dependencies to pick up latest litellm==1.75.0.\r\n\r\n- Aider wrote 88% of the code in this release.",
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Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
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docs/research/aider-ai-aider/raw/github-readme.raw.md.txt
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<p align="center">
<a href="https://aider.chat/"><img src="https://aider.chat/assets/logo.svg" alt="Aider Logo" width="300"></a>
</p>
<h1 align="center">
AI Pair Programming in Your Terminal
</h1>
<p align="center">
Aider lets you pair program with LLMs to start a new project or build on your existing codebase.
</p>
<p align="center">
<img
src="https://aider.chat/assets/screencast.svg"
alt="aider screencast"
>
</p>
<p align="center">
<!--[[[cog
from scripts.homepage import get_badges_md
text = get_badges_md()
cog.out(text)
]]]-->
<a href="https://github.com/Aider-AI/aider/stargazers"><img alt="GitHub Stars" title="Total number of GitHub stars the Aider project has received"
src="https://img.shields.io/github/stars/Aider-AI/aider?style=flat-square&logo=github&color=f1c40f&labelColor=555555"/></a>
<a href="https://pypi.org/project/aider-chat/"><img alt="PyPI Downloads" title="Total number of installations via pip from PyPI"
src="https://img.shields.io/badge/📦%20Installs-6.8M-2ecc71?style=flat-square&labelColor=555555"/></a>
<img alt="Tokens per week" title="Number of tokens processed weekly by Aider users"
src="https://img.shields.io/badge/📈%20Tokens%2Fweek-15B-3498db?style=flat-square&labelColor=555555"/>
<a href="https://openrouter.ai/#options-menu"><img alt="OpenRouter Ranking" title="Aider's ranking among applications on the OpenRouter platform"
src="https://img.shields.io/badge/🏆%20OpenRouter-Top%2020-9b59b6?style=flat-square&labelColor=555555"/></a>
<a href="https://aider.chat/HISTORY.html"><img alt="Singularity" title="Percentage of the new code in Aider's last release written by Aider itself"
src="https://img.shields.io/badge/🔄%20Singularity-88%25-e74c3c?style=flat-square&labelColor=555555"/></a>
<!--[[[end]]]-->
</p>
## Features
### [Cloud and local LLMs](https://aider.chat/docs/llms.html)
<a href="https://aider.chat/docs/llms.html"><img src="https://aider.chat/assets/icons/brain.svg" width="32" height="32" align="left" valign="middle" style="margin-right:10px"></a>
Aider works best with Claude 3.7 Sonnet, DeepSeek R1 & Chat V3, OpenAI o1, o3-mini & GPT-4o, but can connect to almost any LLM, including local models.
<br>
### [Maps your codebase](https://aider.chat/docs/repomap.html)
<a href="https://aider.chat/docs/repomap.html"><img src="https://aider.chat/assets/icons/map-outline.svg" width="32" height="32" align="left" valign="middle" style="margin-right:10px"></a>
Aider makes a map of your entire codebase, which helps it work well in larger projects.
<br>
### [100+ code languages](https://aider.chat/docs/languages.html)
<a href="https://aider.chat/docs/languages.html"><img src="https://aider.chat/assets/icons/code-tags.svg" width="32" height="32" align="left" valign="middle" style="margin-right:10px"></a>
Aider works with most popular programming languages: python, javascript, rust, ruby, go, cpp, php, html, css, and dozens more.
<br>
### [Git integration](https://aider.chat/docs/git.html)
<a href="https://aider.chat/docs/git.html"><img src="https://aider.chat/assets/icons/source-branch.svg" width="32" height="32" align="left" valign="middle" style="margin-right:10px"></a>
Aider automatically commits changes with sensible commit messages. Use familiar git tools to easily diff, manage and undo AI changes.
<br>
### [Use in your IDE](https://aider.chat/docs/usage/watch.html)
<a href="https://aider.chat/docs/usage/watch.html"><img src="https://aider.chat/assets/icons/monitor.svg" width="32" height="32" align="left" valign="middle" style="margin-right:10px"></a>
Use aider from within your favorite IDE or editor. Ask for changes by adding comments to your code and aider will get to work.
<br>
### [Images & web pages](https://aider.chat/docs/usage/images-urls.html)
<a href="https://aider.chat/docs/usage/images-urls.html"><img src="https://aider.chat/assets/icons/image-multiple.svg" width="32" height="32" align="left" valign="middle" style="margin-right:10px"></a>
Add images and web pages to the chat to provide visual context, screenshots, reference docs, etc.
<br>
### [Voice-to-code](https://aider.chat/docs/usage/voice.html)
<a href="https://aider.chat/docs/usage/voice.html"><img src="https://aider.chat/assets/icons/microphone.svg" width="32" height="32" align="left" valign="middle" style="margin-right:10px"></a>
Speak with aider about your code! Request new features, test cases or bug fixes using your voice and let aider implement the changes.
<br>
### [Linting & testing](https://aider.chat/docs/usage/lint-test.html)
<a href="https://aider.chat/docs/usage/lint-test.html"><img src="https://aider.chat/assets/icons/check-all.svg" width="32" height="32" align="left" valign="middle" style="margin-right:10px"></a>
Automatically lint and test your code every time aider makes changes. Aider can fix problems detected by your linters and test suites.
<br>
### [Copy/paste to web chat](https://aider.chat/docs/usage/copypaste.html)
<a href="https://aider.chat/docs/usage/copypaste.html"><img src="https://aider.chat/assets/icons/content-copy.svg" width="32" height="32" align="left" valign="middle" style="margin-right:10px"></a>
Work with any LLM via its web chat interface. Aider streamlines copy/pasting code context and edits back and forth with a browser.
## Getting Started
```bash
python -m pip install aider-install
aider-install
# Change directory into your codebase
cd /to/your/project
# DeepSeek
aider --model deepseek --api-key deepseek=<key>
# Claude 3.7 Sonnet
aider --model sonnet --api-key anthropic=<key>
# o3-mini
aider --model o3-mini --api-key openai=<key>
```
See the [installation instructions](https://aider.chat/docs/install.html) and [usage documentation](https://aider.chat/docs/usage.html) for more details.
## More Information
### Documentation
- [Installation Guide](https://aider.chat/docs/install.html)
- [Usage Guide](https://aider.chat/docs/usage.html)
- [Tutorial Videos](https://aider.chat/docs/usage/tutorials.html)
- [Connecting to LLMs](https://aider.chat/docs/llms.html)
- [Configuration Options](https://aider.chat/docs/config.html)
- [Troubleshooting](https://aider.chat/docs/troubleshooting.html)
- [FAQ](https://aider.chat/docs/faq.html)
### Community & Resources
- [LLM Leaderboards](https://aider.chat/docs/leaderboards/)
- [GitHub Repository](https://github.com/Aider-AI/aider)
- [Discord Community](https://discord.gg/Y7X7bhMQFV)
- [Release notes](https://aider.chat/HISTORY.html)
- [Blog](https://aider.chat/blog/)
## Kind Words From Users
- *"My life has changed... Aider... It's going to rock your world."* — [Eric S. Raymond on X](https://x.com/esrtweet/status/1910809356381413593)
- *"The best free open source AI coding assistant."* — [IndyDevDan on YouTube](https://youtu.be/YALpX8oOn78)
- *"The best AI coding assistant so far."* — [Matthew Berman on YouTube](https://www.youtube.com/watch?v=df8afeb1FY8)
- *"Aider ... has easily quadrupled my coding productivity."* — [SOLAR_FIELDS on Hacker News](https://news.ycombinator.com/item?id=36212100)
- *"It's a cool workflow... Aider's ergonomics are perfect for me."* — [qup on Hacker News](https://news.ycombinator.com/item?id=38185326)
- *"It's really like having your senior developer live right in your Git repo - truly amazing!"* — [rappster on GitHub](https://github.com/Aider-AI/aider/issues/124)
- *"What an amazing tool. It's incredible."* — [valyagolev on GitHub](https://github.com/Aider-AI/aider/issues/6#issue-1722897858)
- *"Aider is such an astounding thing!"* — [cgrothaus on GitHub](https://github.com/Aider-AI/aider/issues/82#issuecomment-1631876700)
- *"It was WAY faster than I would be getting off the ground and making the first few working versions."* — [Daniel Feldman on X](https://twitter.com/d_feldman/status/1662295077387923456)
- *"THANK YOU for Aider! It really feels like a glimpse into the future of coding."* — [derwiki on Hacker News](https://news.ycombinator.com/item?id=38205643)
- *"It's just amazing. It is freeing me to do things I felt were out my comfort zone before."* — [Dougie on Discord](https://discord.com/channels/1131200896827654144/1174002618058678323/1174084556257775656)
- *"This project is stellar."* — [funkytaco on GitHub](https://github.com/Aider-AI/aider/issues/112#issuecomment-1637429008)
- *"Amazing project, definitely the best AI coding assistant I've used."* — [joshuavial on GitHub](https://github.com/Aider-AI/aider/issues/84)
- *"I absolutely love using Aider ... It makes software development feel so much lighter as an experience."* — [principalideal0 on Discord](https://discord.com/channels/1131200896827654144/1133421607499595858/1229689636012691468)
- *"I have been recovering from ... surgeries ... aider ... has allowed me to continue productivity."* — [codeninja on Reddit](https://www.reddit.com/r/OpenAI/s/nmNwkHy1zG)
- *"I am an aider addict. I'm getting so much more work done, but in less time."* — [dandandan on Discord](https://discord.com/channels/1131200896827654144/1131200896827654149/1135913253483069470)
- *"Aider... blows everything else out of the water hands down, there's no competition whatsoever."* — [SystemSculpt on Discord](https://discord.com/channels/1131200896827654144/1131200896827654149/1178736602797846548)
- *"Aider is amazing, coupled with Sonnet 3.5 it's quite mind blowing."* — [Josh Dingus on Discord](https://discord.com/channels/1131200896827654144/1133060684540813372/1262374225298198548)
- *"Hands down, this is the best AI coding assistant tool so far."* — [IndyDevDan on YouTube](https://www.youtube.com/watch?v=MPYFPvxfGZs)
- *"[Aider] changed my daily coding workflows. It's mind-blowing how ...(it)... can change your life."* — [maledorak on Discord](https://discord.com/channels/1131200896827654144/1131200896827654149/1258453375620747264)
- *"Best agent for actual dev work in existing codebases."* — [Nick Dobos on X](https://twitter.com/NickADobos/status/1690408967963652097?s=20)
- *"One of my favorite pieces of software. Blazing trails on new paradigms!"* — [Chris Wall on X](https://x.com/chris65536/status/1905053299251798432)
- *"Aider has been revolutionary for me and my work."* — [Starry Hope on X](https://x.com/starryhopeblog/status/1904985812137132056)
- *"Try aider! One of the best ways to vibe code."* — [Chris Wall on X](https://x.com/Chris65536/status/1905053418961391929)
- *"Freaking love Aider."* — [hztar on Hacker News](https://news.ycombinator.com/item?id=44035015)
- *"Aider is hands down the best. And it's free and opensource."* — [AriyaSavakaLurker on Reddit](https://www.reddit.com/r/ChatGPTCoding/comments/1ik16y6/whats_your_take_on_aider/mbip39n/)
- *"Aider is also my best friend."* — [jzn21 on Reddit](https://www.reddit.com/r/ChatGPTCoding/comments/1heuvuo/aider_vs_cline_vs_windsurf_vs_cursor/m27dcnb/)
- *"Try Aider, it's worth it."* — [jorgejhms on Reddit](https://www.reddit.com/r/ChatGPTCoding/comments/1heuvuo/aider_vs_cline_vs_windsurf_vs_cursor/m27cp99/)
- *"I like aider :)"* — [Chenwei Cui on X](https://x.com/ccui42/status/1904965344999145698)
- *"Aider is the precision tool of LLM code gen... Minimal, thoughtful and capable of surgical changes ... while keeping the developer in control."* — [Reilly Sweetland on X](https://x.com/rsweetland/status/1904963807237259586)
- *"Cannot believe aider vibe coded a 650 LOC feature across service and cli today in 1 shot."* - [autopoietist on Discord](https://discord.com/channels/1131200896827654144/1131200896827654149/1355675042259796101)
- *"Oh no the secret is out! Yes, Aider is the best coding tool around. I highly, highly recommend it to anyone."* — [Joshua D Vander Hook on X](https://x.com/jodavaho/status/1911154899057795218)
- *"thanks to aider, i have started and finished three personal projects within the last two days"* — [joseph stalzyn on X](https://x.com/anitaheeder/status/1908338609645904160)
- *"Been using aider as my daily driver for over a year ... I absolutely love the tool, like beyond words."* — [koleok on Discord](https://discord.com/channels/1131200896827654144/1273248471394291754/1356727448372252783)
- *"Aider ... is the tool to benchmark against."* — [BeetleB on Hacker News](https://news.ycombinator.com/item?id=43930201)
- *"aider is really cool"* — [kache on X](https://x.com/yacineMTB/status/1911224442430124387)
docs/research/aider-ai-aider/raw/github-repo.raw.json
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docs/research/aider-ai-aider/raw/sources.yml
-37
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@@ -1,37 +0,0 @@
version: 1
domain_id: aider-ai-aider
object:
type: github_repository
name: Aider-AI/aider
url: https://github.com/Aider-AI/aider
pulled_at: '2026-07-02T22:47:14+00:00'
puller: scripts/fetch-research-raw.py
files:
- path: repository/
kind: git-working-tree
status: ok
source: 'git clone --depth=1 --single-branch --no-tags https://github.com/Aider-AI/aider.git docs/research/aider-ai-aider/raw/repository'
- path: github-repo.raw.json
kind: repository-metadata
status: ok
source: 'gh repo view Aider-AI/aider --json nameWithOwner,url,description,homepageUrl,isArchived,isFork,isMirror,defaultBranchRef,licenseInfo,primaryLanguage,repositoryTopics,stargazerCount,forkCount,watchers,createdAt,updatedAt,pushedAt,latestRelease --jq .'
- path: github-readme.raw.md.txt
kind: readme
status: ok
source: 'gh api repos/Aider-AI/aider/readme -H Accept: application/vnd.github.raw'
- path: github-license.raw.txt
kind: license
status: ok
source: 'gh api repos/Aider-AI/aider/license -H Accept: application/vnd.github.raw'
- path: github-root-contents.raw.json
kind: root-contents
status: ok
source: 'gh api repos/Aider-AI/aider/contents'
- path: github-languages.raw.json
kind: languages
status: ok
source: 'gh api repos/Aider-AI/aider/languages'
- path: github-latest-release.raw.json
kind: latest-release
status: ok
source: 'gh api repos/Aider-AI/aider/releases/latest'
docs/research/cline-cline/AGENTS.md
-26
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@@ -1,26 +0,0 @@
# cline/cline 研究域 Agent 指南
本目录维护 `cline/cline` 的独立研究域。
## 目录职责
```text
cline-cline/
├── README.md # 研究域入口和判断层
├── AGENTS.md # 本目录维护规则
├── domain.yml # 事实摘要层：仓库元数据、研究角色、来源证据
├── analysis.md # L1 结构化研究结论、可借鉴点、风险和下一轮任务
├── deep-dive.md # L2 源码/结构深度研究、关键机制和可迁移模式
└── raw/ # 原始事实层：拉取到本地的一手材料快照
```
## 维护规则
- 本目录只研究 `cline/cline`，不要混入其他仓库的横向比较正文。
- 动态事实必须写入 `domain.yml.github_observed`，并更新 `observed_at`。
- `raw/` 保存原始事实层，必须通过 `python3 scripts/fetch-research-raw.py` 刷新。
- 不手工改写 `raw/*.raw.*` 文件；稳定事实摘要再同步到 `domain.yml`。
- README 只写判断、定位、使用方式和后续观察点，不堆外部 README 全文。
- `analysis.md` 写 L1 结构化理解；`deep-dive.md` 写 L2 源码证据、关键机制和可迁移模式。
- 如果需要横向比较，在 `docs/research/README.md` 或新的对比文档中处理，不把本目录重新变成聚合域。
- 修改后运行 `make sync-doc-toc` 和 `make test`。
docs/research/cline-cline/README.md
-58
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@@ -1,58 +0,0 @@
# cline/cline 研究域
## 字多不看
- 本目录研究 `cline/cline` 这个外部仓库。
- 当前优先级：P1；研究角色：IDE/SDK/CLI 自主编码 Agent。
- GitHub 动态事实放在 `domain.yml`，观测日期为 2026-07-03。
## 快速导航
| 文档 | 定位 |
|:---|:---|
| [domain.yml](domain.yml) | 仓库事实快照、研究方向、优先级和来源证据。 |
| [analysis.md](analysis.md) | 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。 |
| [deep-dive.md](deep-dive.md) | L2 源码/结构深度研究、关键机制和可迁移模式。 |
| [AGENTS.md](AGENTS.md) | 本研究域维护规则。 |
<details>
<summary><strong>完整细粒度目录（点击展开/收起）</strong></summary>
### 细粒度目录
- [domain.yml](domain.yml) - 仓库事实快照、研究方向、优先级和来源证据。
- [analysis.md](analysis.md) - 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。
- [deep-dive.md](deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [AGENTS.md](AGENTS.md) - 本研究域维护规则。
</details>
## 使用方式
- 先读本 README 的判断，再读 `analysis.md` 和 `deep-dive.md` 的研究结论，最后读 `domain.yml`。
- 需要引用 stars、forks、release、归档状态时，先重新核验 GitHub。
- 如果形成稳定方法论，再迁入 concepts、references、workflow 或 skills。
## 正文
### 研究定位
`cline/cline` 的当前研究定位是：IDE/SDK/CLI 自主编码 Agent。
### 当前判断
适合研究 IDE 内 agent、跨文件修改、工具调用和错误反馈闭环。
### 观察字段
- GitHub URL：https://github.com/cline/cline
- 当前研究方向：`coding-agent-tooling`
- 当前优先级：P1
- 当前归档状态：`false`
- 主要语言：`TypeScript`
### 后续观察
- 是否有稳定文档结构、命令入口和可复用工作流。
- 是否能反哺本仓库的 concepts、references、workflow 或 skills。
- 是否存在许可证、归档状态、维护活跃度或生态迁移风险。
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# cline/cline 研究分析
## 本轮结论
`cline/cline` 的核心价值不是“VS Code 插件怎么做”，而是展示了成熟 agent 产品会从单入口扩展成
IDE、CLI、SDK、rules、skills、examples、evals 和发布脚本共同组成的平台。
本仓最应该迁移的是入口契约：人类阅读入口、AI 上下文入口、脚本入口、skill 入口、资源入口和
metadata 入口不能各自为政，必须写清输入、输出、owner、验证命令和更新策略。
## 本地证据
- 研究对象：`cline/cline`
- 当前研究角色：IDE/SDK/CLI 自主编码 Agent
- 原始仓库：`raw/repository/`
- 原始来源清单：`raw/sources.yml`
- 事实摘要：`domain.yml`
- 深度证据：`deep-dive.md`
## 对标拆解
| 项 | 内容 |
|:---|:---|
| 参考对象 | `cline/cline` |
| 它解决的核心问题 | 让 agent 能力跨 IDE、CLI、SDK、规则、技能、示例和评估保持一致 |
| 核心机制 | `apps/` 多入口，`sdk/` 可复用能力，`.clinerules/` 规则，`.agents/skills` 技能，`evals/` 评估 |
| 真正带来结果的动作 | 把入口和规则文件化，让不同使用表面共享同一套行为边界 |
| 可迁移做法 | 为本仓所有入口建立入口矩阵和更新契约 |
| 不可迁移条件 | 不复制 VS Code 插件、SDK、hub 服务或复杂前端 UI |
| 下一步试用动作 | 梳理人类入口、AI 入口、脚本入口、skill 入口、资源入口和 metadata 入口 |
## 改良迭代
| 改良目标 | 原模式 | 本仓版本 | 验证指标 |
|:---|:---|:---|:---|
| 多入口一致性 | Cline 用 apps/sdk/rules/examples 承载不同入口 | 本仓用 README、AGENTS、llms、metadata、scripts、skills 协同 | 新入口新增时能找到 owner 和验证命令 |
| 规则文件化 | Cline 用 `.clinerules/` 固化 agent 行为 | 本仓用根和目录级 `AGENTS.md` 固化规则 | 架构变更后规则同步 |
| 示例驱动 | Cline 用 examples 展示 SDK/agent 用法 | 本仓为关键 workflow 和 skills 增加最小示例 | 用户能按示例复现流程 |
## 可迁移清单
- 写一张入口矩阵：入口、目标读者、输入、输出、owner、验证命令、更新触发。
- 把 `llms.txt`、`llms-full.txt`、`metadata/taxonomy.yml` 作为 AI 入口，而不是附属文件。
- 把 `scripts/` 和 `skills/` 作为执行入口，明确自动执行边界。
- 为关键 workflow 增加最小示例，避免只写原则。
## 不可迁移清单
- 不提前建设 SDK 或 hub 服务。
- 不为“平台感”增加不必要目录和运行时。
- 不把多入口扩张理解成所有能力都要产品化；本仓优先做文档和 Agent 可读入口一致性。
## 验证动作
| 动作 | 成功信号 | 失败信号 |
|:---|:---|:---|
| 建立入口矩阵 | 任意入口变更能找到同步位置 | 新增入口后 README、metadata、llms 漂移 |
| 抽样一个 skill 写清输入输出和验证 | Agent 能按规则触发和验证 | skill 只是 prompt 文本 |
| 抽样一个 workflow 增加最小示例 | 用户能复现流程 | 只能理解原则，不能操作 |
## 沉淀判断
- 稳定结论应下沉到 `docs/references/` 的多入口仓库结构模板或 `docs/workflow/` 的入口维护规则。
- `deep-dive.md` 保留源码证据；本文件负责把证据转成迁移动作。
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# cline/cline 深度研究
## 研究级别
- 当前级别：L2 源码/结构深度研究。
- 研究对象：`cline/cline`。
- 证据来源：本目录 `raw/` 下的 GitHub 元数据、README 快照和本地仓库工作树。
- 观察日期：2026-07-03。
## L2 结论
`cline/cline` 已经不是单一 VS Code 插件，而是向多入口 agent 平台演化的代码库。它同时包含
VS Code 扩展、CLI、hub 服务、SDK、示例应用、规则系统、技能入口、测试平台和发布脚本。
对本仓最重要的启发是：当 AI coding 工具成熟后，产品边界会从“一个插件”扩展为
IDE、CLI、SDK、hooks、规则、技能、示例和测试平台组成的系统。也就是说，agent 能力必须被
平台化和契约化，不能只依赖单个入口。
## 源码证据
- `raw/repository/apps/vscode/src/extension.ts`：VS Code 扩展入口。
- `raw/repository/apps/vscode/webview-ui/`：前端交互界面。
- `raw/repository/apps/cli/src/main.ts`：CLI 入口。
- `raw/repository/apps/cli/src/index.ts`：CLI 对外模块入口。
- `raw/repository/apps/cline-hub/src/server.ts`：hub 服务入口。
- `raw/repository/apps/cline-hub/src/webview-protocol.ts`：webview 协议边界。
- `raw/repository/sdk/ARCHITECTURE.md`：SDK 架构说明。
- `raw/repository/sdk/AGENTS.md`：SDK 目录的 Agent 维护规则。
- `raw/repository/apps/examples/multi-agent/README.md`：多 agent 示例。
- `raw/repository/apps/examples/code-review-bot/README.md`：代码审查机器人示例。
- `raw/repository/.clinerules/general.md`：项目级规则示例。
- `raw/repository/.agents/skills/cline-sdk/SKILL.md`：技能化能力入口。
## 关键机制
### 多入口产品结构
Cline 同时维护 IDE、CLI、hub 和 SDK。这个结构说明 agent 产品的用户入口会多样化：
开发者可能在编辑器里交互，也可能在终端、自动化服务或自定义应用里调用同一套能力。
### SDK 化是生态扩展前提
`sdk/` 和 examples 表明 Cline 不只服务自己的 UI，还希望让外部开发者复用能力。成熟 agent
生态需要 SDK、示例、协议和测试，而不是只暴露一个不可组合的插件。
### 规则、技能和 hooks 承载操作边界
`.clinerules/`、`.agents/skills/` 和相关配置说明，agent 的行为边界需要显式文件承载。
这与本仓的 `AGENTS.md`、`skills/` 和治理文档方向一致。
### 测试平台和发布脚本是产品能力
当 agent 工具跨 IDE、CLI 和 SDK 后，测试与发布不再是附属流程，而是维持平台一致性的必要
控制面。没有测试平台，多入口很快会出现行为漂移。
## 可迁移模式
- 把本仓能力区分为人类阅读入口、AI 上下文入口、脚本入口和 skill 入口。
- 对每个入口说明协议、输入、输出、风险和验证方式。
- 为重要工作流提供 examples，而不是只写抽象原则。
- 把规则文件、skills、hooks、CLI 和文档索引视为同一套 agent 平台的不同表面。
- 长期考虑为本仓沉淀可复用 SDK/CLI 风格的读取与校验工具。
## 对本仓的影响
本仓已经有 `docs/`、`prompts/`、`skills/`、`scripts/`、`metadata/`、`assets/ai-citation/` 等多个入口。
Cline 的结构提醒我们：这些入口不能各自为政，应该用统一契约说明它们如何协同。
当前最值得推进的是：
- `metadata/` 继续作为机器索引事实源。
- `llms.txt` 和 `assets/ai-citation/llms-full.txt` 继续作为 AI 读取入口。
- `scripts/` 继续作为仓库控制面。
- `skills/` 继续作为 Agent 可复用能力层。
- `docs/research/` 继续作为研究对象网络。
## 风险和待验证项
- Cline 代码库较大，且产品线较多；本轮没有验证所有 package 的构建和测试。
- 多入口平台化会带来复杂度，本仓不应为了“看起来平台化”提前增加不必要代码。
- 本仓当前仍以文档知识库为主，迁移时应优先吸收契约和治理模式，而非复制应用结构。
## 下一步 L3 验证任务
- 梳理本仓所有入口：人类入口、AI 入口、脚本入口、skill 入口、资源入口。
- 为每类入口写清输入、输出、owner、验证命令和更新策略。
- 在 `docs/references/` 中沉淀“多入口 agent 仓库结构模板”。
- 用 Cline examples 的思路，为本仓关键工作流增加最小可运行示例。
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version: 1
repo:
name: cline/cline
source_name: cline/cline
url: https://github.com/cline/cline
research:
domain_id: cline-cline
domain_name: cline/cline 研究域
primary_direction: coding-agent-tooling
role: IDE/SDK/CLI 自主编码 Agent
priority: 1
why_study: 适合研究 IDE 内 agent、跨文件修改、工具调用和错误反馈闭环。
github_observed:
observed_at: '2026-07-03'
source: gh repo view
stars: 64218
forks: 6822
archived: false
language: TypeScript
license: apache-2.0
default_branch: main
pushed_at: '2026-07-02T21:53:59Z'
updated_at: '2026-07-02T20:47:18Z'
latest_release: v4.0.6
homepage: https://cline.bot
topics: []
source_evidence:
file: ChatGPT-中文Vibe Coding仓库 (2).md
line: 58
maintenance:
fact_policy: GitHub 动态字段只代表 observed_at 当日快照，更新结论前必须重新核验。
split_policy: 本目录已经是一等研究域；更深分析放入本目录新增文档。
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# raw/ Agent 指南
本目录是 `cline/cline` 的原始事实层。
## 维护规则
- 只保存从研究对象拉取的一手材料，不写分析判断。
- `repository/` 是本地 Git 工作树，刷新时由脚本 clone 或 fast-forward pull。
- 不手工改写 `*.raw.*` 文件内容；需要刷新时运行 `python3 scripts/fetch-research-raw.py`。
- `sources.yml` 必须记录拉取时间、来源命令和每个文件的状态。
- 外部 README 原文必须保存为 `.txt`，避免本仓库 Markdown 链接检查误判。
- 分析、判断、采用建议和沉淀路径写回上一级 `README.md`、`analysis.md` 或 `decisions.md`。
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# raw 事实层
本目录保存 `cline/cline` 的本地原始材料快照。
这里不写分析结论，只保存可复查的一手资料：
- `sources.yml`：来源清单、拉取时间、命令和文件状态。
- `repository/`：Git 仓库工作树；本目录由 `.gitignore` 忽略，只作为本地研究材料。
- `github-repo.raw.json`：GitHub 仓库元数据。
- `github-readme.raw.md.txt`：GitHub README 原文快照。
- `github-license.raw.txt`：GitHub license 原文快照；仓库无 license 时可能不存在。
- `github-root-contents.raw.json`：默认分支根目录内容快照。
- `github-languages.raw.json`：GitHub language 统计快照。
- `github-latest-release.raw.json`：最新 release 快照；无 release 时可能不存在。
`repository/` 是外部源码快照，不参与本仓库 Markdown、链接、README/AGENTS 覆盖检查。原始 README 使用 `.txt` 后缀保存，避免其中的外部相对链接被本仓库 Markdown 链接检查误判。
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9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
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License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
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END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. We also recommend that a
file or class name and description of purpose be included on the
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright 2026 Cline Bot Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
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Unless required by applicable law or agreed to in writing, software
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docs/research/cline-cline/raw/github-readme.raw.md.txt
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<p align="center">
<img src="assets/icons/icon.png" width="80" alt="Cline" />
</p>
<h1 align="center">Cline</h1>
<p align="center">
The open source coding agent in your IDE and terminal.
</p>
<div align="center">
<div align="center">
<table>
<tbody>
<td align="center">
<a href="https://docs.cline.bot" target="_blank"><strong>Docs</strong></a>
</td>
<td align="center">
<a href="https://discord.gg/cline" target="_blank"><strong>Discord</strong></a>
</td>
<td align="center">
<a href="https://www.reddit.com/r/cline/" target="_blank"><strong>r/cline</strong></a>
</td>
<td align="center">
<a href="https://github.com/cline/cline/discussions/categories/feature-requests?discussions_q=is%3Aopen+category%3A%22Feature+Requests%22+sort%3Atop" target="_blank"><strong>Feature Requests</strong></a>
</td>
<td align="center">
<a href="https://cline.bot/join-us" target="_blank"><strong>Join us!</strong></a>
</td>
</tbody>
</table>
</div>
</div>
<br>
<div align="center">
<table>
<tr>
<td align="center" width="50%">
### CLI
Run Cline in your terminal.
Interactive chat or fully headless
for CI/CD and scripting.
```
npm i -g cline
```
<a href="./apps/cli/README.md">Learn more</a>
<br><br>
</td>
<td align="center" width="50%">
### Kanban
Run many agents in parallel from a
web-based task board. Each card gets its own
worktree, auto-commit, and dependency chains.
```
npm i -g kanban
```
<a href="https://github.com/cline/kanban">Learn more</a>
<br><br>
</td>
</tr>
<tr>
<td align="center" width="50%">
### VS Code Extension
AI coding assistant in your editor.
Create files, run commands, browse the web,
and use tools with human-in-the-loop approval.
<a href="https://marketplace.visualstudio.com/items?itemName=saoudrizwan.claude-dev">Install from VS Marketplace</a>
<br><br>
</td>
<td align="center" width="50%">
### JetBrains Plugin
The same Cline experience in IntelliJ IDEA,
PyCharm, WebStorm, GoLand, and the rest of
the JetBrains family.
<a href="https://plugins.jetbrains.com/plugin/28247-cline">Install from JetBrains Marketplace</a>
<br><br>
</td>
</tr>
</table>
</div>
<div align="center">
<table>
<tr>
<td align="center">
### SDK
Build your own AI agents and integrations powered by the same engine that runs the CLI, Kanban, VS Code extension, and JetBrains plugin. Custom tools, multi-agent teams, connectors, scheduled automations, and more.
```
npm install @cline/sdk
```
<a href="https://docs.cline.bot/cline-sdk/overview">Documentation</a>
<br><br>
</td>
</tr>
</table>
</div>
---
## Index
| Product | Description | Location | CHANGELOG |
|---------|------------|--------------|--------------|
| **SDK** | Node.js programmatic agent API and extension exports. | [`sdk/`](https://github.com/cline/cline/tree/main/sdk) | [CHANGELOG.md](https://github.com/cline/cline/blob/main/sdk/CHANGELOG.md) |
| **CLI** | Terminal UI, headless mode, shell commands, and CLI-specific flows. | [`apps/cli/`](https://github.com/cline/cline/tree/main/apps/cli) | [CHANGELOG.md](https://github.com/cline/cline/blob/main/apps/cli/CHANGELOG.md) |
| **VS Code Extension** | The Marketplace extension and extension host integration. | [`/`](https://github.com/cline/cline/tree/main) (WIP migrating) | [CHANGELOG.md](https://github.com/cline/cline/blob/main/CHANGELOG.md) |
| **JetBrains Plugin** | JetBrains-hosted client that talks to the shared agent core. | Currently we are not open-sourcing JetBrains plugins | - |
| **Kanban** | Web-based multi-agent task board. | [`cline/kanban`](https://github.com/cline/kanban) | [CHANGELOG.md](https://github.com/cline/kanban/blob/main/CHANGELOG.md) |
| **Docs site** | Public documentation pages. | [`docs/`](https://docs.cline.bot/) | - |
## Edits Code Across Your Project
Cline reads your project structure, understands the relationships between files, and makes coordinated changes across your codebase. It monitors linter and compiler errors as it works, fixing issues like missing imports, type mismatches, and syntax errors before you even see them. In VS Code and JetBrains, every edit shows up as a diff you can review, modify, or revert. All changes are tracked with checkpoints, so you can easily undo the agent's work.
## Runs Bash Commands
Cline executes commands directly in your terminal and watches the output in real time. Install packages, run build scripts, execute tests, deploy applications, manage databases. For long-running processes like dev servers, Cline continues working in the background and reacts to new output as it appears, catching compile errors, test failures, and server crashes as they happen.
## Plan and Act
Toggle between Plan mode and Act mode. In Plan mode, Cline explores your codebase, asks clarifying questions, and lays out a strategy. Once you're aligned, switch to Act mode and Cline executes the plan. Every file edit and terminal command requires your approval, so you stay in control of what actually changes. Or toggle auto-approve and let Cline run autonomously.
## Rules and Skills
Define project-specific rules in `.clinerules` files that guide how Cline works in your codebase: coding standards, architecture conventions, deployment procedures, testing requirements. Rules are picked up automatically by the CLI, VS Code extension, and JetBrains plugin. Use skills to let the model load specific rules when needed.
## Works With Every Model
Cline is not locked to a single AI provider. Use whichever model fits your workflow:
| Provider | Models |
|----------|--------|
| Anthropic | Claude Opus, Sonnet, Haiku |
| OpenAI | GPT series model |
| Google | Gemini series model |
| OpenRouter | 200+ models from any provider |
| Vercel AI Gateway | Models through Vercel AI Gateway |
| AWS Bedrock | Claude, Llama, and more |
| Azure / GCP Vertex | All hosted models |
| Cerebras / Groq | Fast inference models |
| Ollama / LM Studio | Run local models on your machine |
| Any OpenAI-compatible API | Self-hosted or third-party endpoints |
## Extend With Plugins or MCP Servers
Extend Cline's capabilities with plugins. Using the SDK, register tools and lifecycle hooks programmatically through the plugin system for logging, auditing, policy enforcement, or adding domain-specific capabilities. Simple plugin example below.
```typescript
import { Agent, createTool } from "@cline/sdk"
const deployTool = createTool({
name: "deploy",
description: "Deploy the current branch to staging.",
inputSchema: { type: "object", properties: { env: { type: "string" } }, required: ["env"] },
execute: async (input) => {
// your deployment logic
},
})
const agent = new Agent({ tools: [deployTool], /* ... */ })
```
...or use [MCP servers](https://github.com/modelcontextprotocol) to connect to databases, query APIs, manage cloud infrastructure, and interact with external systems. Use [community-built servers](https://github.com/modelcontextprotocol/servers) or ask Cline to create custom tools on the fly. In the CLI, manage servers with `cline mcp`.
## Multi-Agent Teams
Coordinate multiple agents working together on complex tasks. A coordinator agent breaks the work into subtasks and delegates to specialist agents, each with their own tools and context. Team state persists across sessions so you can pick up where you left off.
```bash
cline --team-name auth-sprint "Plan and implement user authentication with tests"
```
## Scheduled Agents
Run agents on cron schedules for recurring automations. Daily PR summaries, weekly dependency checks, codebase health reports. Schedules persist across restarts and run independently of any terminal session.
```bash
cline schedule create "PR summary" \
--cron "0 9 * * MON-FRI" \
--prompt "List all open PRs and their review status" \
--workspace /path/to/repo
```
## Connect to Slack, Telegram, Discord, and More
Chat with your agent from any messaging platform: Telegram, Slack, Discord, Google Chat, WhatsApp, and Linear. Each conversation thread maps to an agent session with full context. Set up access control to restrict who can interact with your agent.
```bash
# Connect to Telegram
cline connect telegram -k $BOT_TOKEN
# Connect to Slack through webhook
cline connect slack --bot-token $SLACK_TOKEN --signing-secret $SECRET --base-url $URL
# Connect to Slack using socket mode
cline connect slack --bot-token $SLACK_TOKEN --app-token $SLACK_APP_TOKEN
```
## Headless CLI for CI/CD
Run Cline with zero interaction for scripting and automation. Pipe input, get JSON output, chain commands, integrate into CI/CD pipelines.
```bash
cline "Run tests and fix any failures"
git diff origin/main | cline "Review these changes for issues"
cline --json "List all TODO comments" | jq -r 'select(.type == "agent_event" and .event.text) | .event.text'
```
## Contributing
Start with the [Contributing Guide](CONTRIBUTING.md). Join our [Discord](https://discord.gg/cline) and head to the `#contributors` channel to connect with other contributors. Check our [careers page](https://cline.bot/join-us) for full-time roles.
## License
[Apache 2.0 © 2026 Cline Bot Inc.](./LICENSE)
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docs/research/cline-cline/raw/sources.yml
-37
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@@ -1,37 +0,0 @@
version: 1
domain_id: cline-cline
object:
type: github_repository
name: cline/cline
url: https://github.com/cline/cline
pulled_at: '2026-07-02T22:47:14+00:00'
puller: scripts/fetch-research-raw.py
files:
- path: repository/
kind: git-working-tree
status: ok
source: 'git clone --depth=1 --single-branch --no-tags https://github.com/cline/cline.git docs/research/cline-cline/raw/repository'
- path: github-repo.raw.json
kind: repository-metadata
status: ok
source: 'gh repo view cline/cline --json nameWithOwner,url,description,homepageUrl,isArchived,isFork,isMirror,defaultBranchRef,licenseInfo,primaryLanguage,repositoryTopics,stargazerCount,forkCount,watchers,createdAt,updatedAt,pushedAt,latestRelease --jq .'
- path: github-readme.raw.md.txt
kind: readme
status: ok
source: 'gh api repos/cline/cline/readme -H Accept: application/vnd.github.raw'
- path: github-license.raw.txt
kind: license
status: ok
source: 'gh api repos/cline/cline/license -H Accept: application/vnd.github.raw'
- path: github-root-contents.raw.json
kind: root-contents
status: ok
source: 'gh api repos/cline/cline/contents'
- path: github-languages.raw.json
kind: languages
status: ok
source: 'gh api repos/cline/cline/languages'
- path: github-latest-release.raw.json
kind: latest-release
status: ok
source: 'gh api repos/cline/cline/releases/latest'
docs/research/daotin-ai-coding/AGENTS.md
-24
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@@ -1,24 +0,0 @@
# Daotin/ai-coding 研究域 Agent 指南
本目录维护 `Daotin/ai-coding` 的独立研究域。
## 目录职责
```text
daotin-ai-coding/
├── README.md # 研究域入口和判断层
├── AGENTS.md # 本目录维护规则
├── domain.yml # 事实摘要层：仓库元数据、研究角色、来源证据
├── deep-dive.md # L2 结构深度研究、关键机制、迁移边界和验证任务
└── raw/ # 原始事实层：拉取到本地的一手材料快照
```
## 维护规则
- 本目录只研究 `Daotin/ai-coding`，不要混入其他仓库的横向比较正文。
- 动态事实必须写入 `domain.yml.github_observed`，并更新 `observed_at`。
- `raw/` 保存原始事实层，必须通过 `python3 scripts/fetch-research-raw.py` 刷新。
- 不手工改写 `raw/*.raw.*` 文件；稳定事实摘要再同步到 `domain.yml`。
- README 只写判断、定位、使用方式和后续观察点，不堆外部 README 全文。
- 如果需要横向比较，在 `docs/research/README.md` 或新的对比文档中处理，不把本目录重新变成聚合域。
- 修改后运行 `make sync-doc-toc` 和 `make test`。
docs/research/daotin-ai-coding/README.md
-59
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@@ -1,59 +0,0 @@
# Daotin/ai-coding 研究域
## 字多不看
- 本目录研究 `Daotin/ai-coding` 这个外部仓库。
- 当前优先级：P3；研究角色：AI Coding 经验汇总。
- GitHub 动态事实放在 `domain.yml`，观测日期为 2026-07-03。
## 快速导航
| 文档 | 定位 |
|:---|:---|
| [domain.yml](domain.yml) | 仓库事实快照、研究方向、优先级和来源证据。 |
| [analysis.md](analysis.md) | 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。 |
| [deep-dive.md](deep-dive.md) | L2 结构深度研究、关键机制、迁移边界和验证任务。 |
| [AGENTS.md](AGENTS.md) | 本研究域维护规则。 |
<details>
<summary><strong>完整细粒度目录（点击展开/收起）</strong></summary>
### 细粒度目录
- [domain.yml](domain.yml) - 仓库事实快照、研究方向、优先级和来源证据。
- [analysis.md](analysis.md) - 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。
- [deep-dive.md](deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [AGENTS.md](AGENTS.md) - 本研究域维护规则。
</details>
## 使用方式
- 先读本 README 的判断，再读 `analysis.md` 的结构化研究结论，再读 `deep-dive.md` 的 L2 证据，
最后读 `domain.yml` 的事实字段。
- 需要引用 stars、forks、release、归档状态时，先重新核验 GitHub。
- 如果形成稳定方法论，再迁入 concepts、references、workflow 或 skills。
## 正文
### 研究定位
`Daotin/ai-coding` 的当前研究定位是：AI Coding 经验汇总。
### 当前判断
适合补充 Cursor、Claude Code、Codex、MCP、AGENTS.md 等实践素材。
### 观察字段
- GitHub URL：https://github.com/Daotin/ai-coding
- 当前研究方向：`workflow-methodology`
- 当前优先级：P3
- 当前归档状态：`false`
- 主要语言：`None`
### 后续观察
- 是否有稳定文档结构、命令入口和可复用工作流。
- 是否能反哺本仓库的 concepts、references、workflow 或 skills。
- 是否存在许可证、归档状态、维护活跃度或生态迁移风险。
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# Daotin/ai-coding 研究分析
## 本轮结论
`Daotin/ai-coding` 的核心价值是中文 AI Coding 主题雷达。它覆盖 Cursor、Claude Code、Codex、MCP、
AGENTS.md、提示词、经验和实战，适合帮助本仓观察中文社区正在关心什么。
本仓不能把它当作工程标准来源。正确用法是：抽取高频主题、关键词和候选资源，再用本仓的 raw、
analysis、deep-dive 和门禁流程二次验证。
## 本地证据
- 研究对象：`Daotin/ai-coding`
- 当前研究角色：AI Coding 经验汇总
- 原始仓库：`raw/repository/`
- 原始来源清单：`raw/sources.yml`
- 事实摘要：`domain.yml`
## 对标拆解
| 项 | 内容 |
|:---|:---|
| 参考对象 | `Daotin/ai-coding` |
| 它解决的核心问题 | 汇总中文 AI Coding 主题、工具和经验入口 |
| 核心机制 | README 多主题索引，覆盖方法论、工具、经验、实战、提示词和 MCP |
| 真正带来结果的动作 | 快速暴露中文社区高频关注点 |
| 可迁移做法 | 关键词候选、资源候选、MCP/AGENTS/Codex/Claude Code 主题雷达 |
| 不可迁移条件 | 不把资料聚合当作验证结论，不复制为本仓标准 |
| 下一步试用动作 | 抽取高频主题并映射到 `docs/concepts/keyword-system.md` |
## 改良迭代
| 改良目标 | 原模式 | 本仓版本 | 验证指标 |
|:---|:---|:---|:---|
| 主题发现 | 多主题资料汇总 | 关键词系统候选和资源注册表候选 | 候选有来源和采用理由 |
| 经验筛选 | 经验链接聚合 | 经验必须转成短句、流程或检查项 | 经验不再只是外链 |
| 工具观察 | 工具清单 | 高价值工具升级为独立研究域 | 升级有优先级和边界 |
## 可迁移清单
- 抽取中文 AI Coding 高频词。
- 观察 MCP、AGENTS.md、Codex、Claude Code 相关资源热度。
- 将高价值资源进入 `assets/external-resources/`。
- 将稳定经验候选进入 `docs/getting-started/` 或 `docs/workflow/`。
## 不可迁移清单
- 不把聚合链接当作采用建议。
- 不让本仓变成资料堆。
- 不把未经验证的经验写入工程规范。
## 验证动作
| 动作 | 成功信号 | 失败信号 |
|:---|:---|:---|
| 抽取 20 个高频关键词 | 关键词能进入概念系统候选 | 关键词无定义和用途 |
| 筛选 10 条资源 | 资源进入本地注册表并有状态 | 只复制链接 |
| 抽取 5 条经验 | 每条转成动作或检查项 | 经验仍是口号 |
## 沉淀判断
- 稳定结果进入关键词系统、外部资源注册表和 workflow。
- 本研究域保持 P3 中文主题雷达。
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# Daotin/ai-coding 深度研究
## 研究级别
- 当前级别：L2 结构深度研究。
- 研究对象：`Daotin/ai-coding`。
- 证据来源：本目录 `raw/` 下的 GitHub 元数据、README 快照、BACKUP 文章镜像和本地仓库工作树。
- 观察日期：2026-07-03。
## L2 结论
`Daotin/ai-coding` 的核心价值是中文 AI Coding 主题雷达。它把 Cursor、Claude Code、Codex、MCP、
AGENTS.md、OpenSkills、BMAD、Figma MCP、Prompt、UI 原型、验证技巧等实践话题集中在 README
和 BACKUP 文章镜像中，适合观察中文社区正在关心什么。
对本仓最重要的启发是：社区经验不能直接当标准，但可以作为关键词、问题清单和下沉任务的来源。
它的价值在“主题发现”，不在“工程规范定稿”。
## 本地证据
- `raw/repository/README.md`：按 AI 方法论、AI 工具、AI 经验、AI 科普、AI 实战、AI 思考、
AI 提示词和 MCP 组织入口。
- `raw/repository/BACKUP/issue-18-ClaudeCode使用教程.md`：Claude Code 相关实践材料。
- `raw/repository/BACKUP/issue-26-Codex使用技巧.md`：Codex 使用技巧材料。
- `raw/repository/BACKUP/issue-41-一文搞懂MCP.md`：MCP 主题材料。
- `raw/repository/BACKUP/issue-44-AGENTS.md.md`：AGENTS.md 主题材料。
- `raw/repository/BACKUP/issue-45-MCP和AgentSkills的核心区别.md`：MCP 与 Agent Skills 对比材料。
- `raw/repository/BACKUP/issue-47-OpenSkills，AI编程助手的"Forge".md`：OpenSkills 主题材料。
- `domain.yml`：当前优先级为 P3，研究方向为 `workflow-methodology`。
## 关键机制
### Issue 到 README 的主题汇总
该仓库把分散文章和 issue 型内容汇总到 README。这个机制适合快速积累主题，但缺少版本化契约、
验证指标和稳定分类。
### 中文高频问题捕获
仓库覆盖了 MCP、AGENTS.md、Claude Code、Codex、BMAD、Figma MCP、Prompt 递归、AI 验证、
UI 原型等高频实践问题。这些主题可以反哺本仓的关键词系统和经验模块。
### 社区经验需要二次工程化
内容是经验集合，不是统一方法论。要进入本仓稳定层，必须重新拆成目的、对象、约束、输入、输出、
验证和失败条件。
## 可迁移模式
- 将 BACKUP 文章视为中文 AI Coding 关键词候选池。
- 把高频主题映射到 `docs/concepts/keyword-system.md`、`docs/workflow/` 和 `skills/`。
- 对 MCP、AGENTS.md、Skills、Codex、Claude Code 等主题建立“问题 -> 概念 -> 操作模板”链路。
- 将用户常见模糊需求整理为面试式 SPEC 生成流程。
- 将“告诉 AI 如何验证”类经验转成验证检查清单。
## 对本仓的影响
本仓可以从这个对象获得三类输入：
- 关键词输入：MCP、AGENTS.md、Agent Skills、BMAD、OpenSkills、Prompt 递归、验证。
- 流程输入：模糊需求访谈、AI 生成 SPEC、AI 自验证、UI 原型到实现。
- 资源输入：中文教程和工具文章候选资源。
这些输入应该进入研究域、关键词系统、资源候选表或 workflow 模板，而不是直接搬运为标准答案。
## 风险和待验证项
- 文章集合的质量不均，不能把单篇观点当作本仓规范。
- 部分主题变化很快，MCP、Codex、Claude Code 和 Skills 相关事实需要重新核验。
- README 聚合不等于治理，缺少状态字段、最后检查时间和验证记录。
- P3 定位应保留，除非某个主题在本仓形成明确采用需求。
## 下一步 L3 验证任务
- 从 BACKUP 中抽取 30 个高频关键词，和本仓关键词系统去重合并。
- 将“模糊需求让 AI 面试你形成 SPEC”整理为 workflow 候选模板。
- 为 MCP、AGENTS.md、Skills 三个主题建立概念边界说明，避免用户混用。
- 将 AI 验证技巧整理成一份最小 Debug 输入契约：预期、实际、最小复现、环境、验证命令。
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version: 1
repo:
name: Daotin/ai-coding
source_name: Daotin/ai-coding
url: https://github.com/Daotin/ai-coding
research:
domain_id: daotin-ai-coding
domain_name: Daotin/ai-coding 研究域
primary_direction: workflow-methodology
role: AI Coding 经验汇总
priority: 3
why_study: 适合补充 Cursor、Claude Code、Codex、MCP、AGENTS.md 等实践素材。
github_observed:
observed_at: '2026-07-03'
source: gh repo view
stars: 65
forks: 6
archived: false
language: null
license: mit
default_branch: main
pushed_at: '2026-01-24T13:27:57Z'
updated_at: '2026-07-02T10:34:32Z'
latest_release: null
homepage: ''
topics: []
source_evidence:
file: ChatGPT-中文Vibe Coding仓库 (2).md
line: 35
maintenance:
fact_policy: GitHub 动态字段只代表 observed_at 当日快照，更新结论前必须重新核验。
split_policy: 本目录已经是一等研究域；更深分析放入本目录新增文档。
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# raw/ Agent 指南
本目录是 `Daotin/ai-coding` 的原始事实层。
## 维护规则
- 只保存从研究对象拉取的一手材料，不写分析判断。
- `repository/` 是本地 Git 工作树，刷新时由脚本 clone 或 fast-forward pull。
- 不手工改写 `*.raw.*` 文件内容；需要刷新时运行 `python3 scripts/fetch-research-raw.py`。
- `sources.yml` 必须记录拉取时间、来源命令和每个文件的状态。
- 外部 README 原文必须保存为 `.txt`，避免本仓库 Markdown 链接检查误判。
- 分析、判断、采用建议和沉淀路径写回上一级 `README.md`、`analysis.md` 或 `decisions.md`。
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# raw 事实层
本目录保存 `Daotin/ai-coding` 的本地原始材料快照。
这里不写分析结论，只保存可复查的一手资料：
- `sources.yml`：来源清单、拉取时间、命令和文件状态。
- `repository/`：Git 仓库工作树；本目录由 `.gitignore` 忽略，只作为本地研究材料。
- `github-repo.raw.json`：GitHub 仓库元数据。
- `github-readme.raw.md.txt`：GitHub README 原文快照。
- `github-license.raw.txt`：GitHub license 原文快照；仓库无 license 时可能不存在。
- `github-root-contents.raw.json`：默认分支根目录内容快照。
- `github-languages.raw.json`：GitHub language 统计快照。
- `github-latest-release.raw.json`：最新 release 快照；无 release 时可能不存在。
`repository/` 是外部源码快照，不参与本仓库 Markdown、链接、README/AGENTS 覆盖检查。原始 README 使用 `.txt` 后缀保存，避免其中的外部相对链接被本仓库 Markdown 链接检查误判。
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@@ -1 +0,0 @@
{}
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MIT License
Copyright (c) 2025 Daotin
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
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# 📚 AI Coding
<!-- UPDATED_AT --> updated: 2026-01-02 21:43:22 <!-- UPDATED_AT -->
## 关于本仓库
一直以来，我对 AI Coding 充满热情和好奇。从最初的探索到如今的深度实践，这一年来，我持续学习各种 AI 辅助编程工具和方法论，并将它们应用到实际项目开发中。
本仓库汇集了我在 AI Coding 领域的：
- **方法论**：从 0 到 1 的实践经验和思考框架
- **实战案例**：真实项目中的 AI 应用场景
- **经验分享**：踩过的坑和总结的技巧
- **提示词技巧**：如何更高效地与 AI 协作
- **工具推荐**：实用的 AI 开发工具和工作流
希望这些内容能够帮助到同样对 AI Coding 感兴趣的朋友们，让我们一起探索 AI 赋能开发的无限可能！
<!-- ISSUES-LIST:START -->
<!-- 此列表由 GitHub Actions 自动生成，请勿手动修改 -->
## AI方法论
* [BMAD——基于Spec-kit理念的AI敏捷开发工作流](https://github.com/Daotin/ai-coding/issues/42) (2025-12-01)
* [AI赋能前端中后台开发](https://github.com/Daotin/ai-coding/issues/11) (2025-10-28)
* [AI Coding的正确范式](https://github.com/Daotin/ai-coding/issues/8) (2025-10-27)
* [AI Coding 维护现有项目](https://github.com/Daotin/ai-coding/issues/5) (2025-10-27)
* [AI Coding从0到1方法论](https://github.com/Daotin/ai-coding/issues/2) (2025-10-27)
## AI工具
* [OpenSkills，AI 编程助手的"Forge"](https://github.com/Daotin/ai-coding/issues/47) (2026-01-24)
* [一文搞懂MCP](https://github.com/Daotin/ai-coding/issues/41) (2025-11-07)
* [一文搞懂cursor](https://github.com/Daotin/ai-coding/issues/40) (2025-11-07)
* [自动化操作MCP](https://github.com/Daotin/ai-coding/issues/20) (2025-10-28)
* [Figma远程MCP](https://github.com/Daotin/ai-coding/issues/19) (2025-10-28)
* [Claude Code使用教程](https://github.com/Daotin/ai-coding/issues/18) (2025-10-28)
* [UI原型图+设计稿+Vibe Coding](https://github.com/Daotin/ai-coding/issues/17) (2025-10-28)
* [最佳AI开发工作流](https://github.com/Daotin/ai-coding/issues/16) (2025-10-28)
* [出海独立开发穷鬼全家桶](https://github.com/Daotin/ai-coding/issues/15) (2025-10-28)
* [UI原型图+设计稿](https://github.com/Daotin/ai-coding/issues/4) (2025-10-27)
## AI经验
* [AGENTS.md](https://github.com/Daotin/ai-coding/issues/44) (2025-12-15)
* [【转】AI Coding 实践技巧，告诉 AI 如何验证](https://github.com/Daotin/ai-coding/issues/38) (2025-11-03)
* [使用json样式设计文件，避免AI生成的页面有一股AI味儿。](https://github.com/Daotin/ai-coding/issues/28) (2025-10-28)
* [Vibe Coding 工作流LLM模型选择](https://github.com/Daotin/ai-coding/issues/27) (2025-10-28)
* [Codex使用技巧](https://github.com/Daotin/ai-coding/issues/26) (2025-10-28)
* [【摘录】AI Coding，其实很像做技术管理](https://github.com/Daotin/ai-coding/issues/9) (2025-10-28)
* [Andrej Karpathy 的 Vibe Coding 技巧](https://github.com/Daotin/ai-coding/issues/7) (2025-10-27)
* [cursor引入外部文档的方式](https://github.com/Daotin/ai-coding/issues/6) (2025-10-27)
## AI科普
* [MCP 和 Agent Skills 的核心区别](https://github.com/Daotin/ai-coding/issues/45) (2025-12-21)
## AI实战
* [Todo](https://github.com/Daotin/ai-coding/issues/36) (2025-10-29)
- [ ] AI+监控系统：监控大屏中，对于错误，增加 AI 修复建议
- [ ] AI+VSCode 插件：自研公司内部 vscode 插件，提效（生成自定义组件，echart，代码辅助等）
- [ ] AI+Agent（参考 [NC VSCode IDE](https://mp.weixin.qq.com/s/GwNnkuDvbDDLjp0MHtypQw)）
- [ ] AI+自动化测试（参考 [使用 CodeX 调起 Chrome-devtools-mcp 做了其中一个关键场景走查](https://x.com/Stephen4171127/status/1972348138628464813)）
* [小红书内容生成器(AI Agent)](https://github.com/Daotin/ai-coding/issues/14) (2025-10-28)
* [AI+游戏设计](https://github.com/Daotin/ai-coding/issues/13) (2025-10-28)
* [MCP原理解析及搭建私有组件库MCP](https://github.com/Daotin/ai-coding/issues/10) (2025-10-28)
* [自动删除 FG](https://github.com/Daotin/ai-coding/issues/1) (2025-10-27)
## AI思考
* [对于模糊的需求，可以让 AI 面试你，通过提问的形式一步步形成 SPEC 文档，然后使用该 SPEC 完成需求开发](https://github.com/Daotin/ai-coding/issues/46) (2026-01-02)
* [AI时代，资深工程师的价值在哪里？](https://github.com/Daotin/ai-coding/issues/39) (2025-11-05)
## AI提示词
* [使用json样式设计文件，避免AI生成的页面有一股AI味儿。](https://github.com/Daotin/ai-coding/issues/28) (2025-10-28)
* [AI洞察](https://github.com/Daotin/ai-coding/issues/25) (2025-10-28)
* [递归法写Prompt](https://github.com/Daotin/ai-coding/issues/24) (2025-10-28)
* [【摘录】为什么我用了那么多提示词模板甚至用了 AI 帮忙还是写不好提示词？](https://github.com/Daotin/ai-coding/issues/23) (2025-10-28)
* [AI+landing page](https://github.com/Daotin/ai-coding/issues/22) (2025-10-28)
* [AI+PPT](https://github.com/Daotin/ai-coding/issues/21) (2025-10-28)
* [AI设计网页svg](https://github.com/Daotin/ai-coding/issues/12) (2025-10-28)
* [APP设计稿](https://github.com/Daotin/ai-coding/issues/3) (2025-10-27)
## MCP
* [Todo](https://github.com/Daotin/ai-coding/issues/37) (2025-10-29)
- [ ] Story MCP：如果你们有 tapd 之类的需求平台，甚至可以自己实现一个 mcp 来让他拉取相对应项目的需求，基于 tapd 上的 story 在本地创建一个 story，做具体的任务拆解，分块完成。
- [ ] Story MCP：通过自己开发的 Jira MCP，连接到自己公司的 Jira 服务器，自动获取 bug，自动修复，自动 run dev 验证，自动 commit。
- [ ] API MCP：连接后端数据库，做前端 mock 代码生成
* [自动化操作MCP](https://github.com/Daotin/ai-coding/issues/20) (2025-10-28)
* [MCP原理解析及搭建私有组件库MCP](https://github.com/Daotin/ai-coding/issues/10) (2025-10-28)
<!-- ISSUES-LIST:END -->
# License
[MIT License](./LICENSE)
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# datawhalechina/easy-vibe 研究域 Agent 指南
本目录维护 `datawhalechina/easy-vibe` 的独立研究域。
## 目录职责
```text
datawhalechina-easy-vibe/
├── README.md # 研究域入口和判断层
├── AGENTS.md # 本目录维护规则
├── domain.yml # 事实摘要层：仓库元数据、研究角色、来源证据
├── analysis.md # L1 结构化研究结论、可借鉴点、风险和下一轮任务
├── deep-dive.md # L2 源码/结构深度研究、关键机制和可迁移模式
└── raw/ # 原始事实层：拉取到本地的一手材料快照
```
## 维护规则
- 本目录只研究 `datawhalechina/easy-vibe`，不要混入其他仓库的横向比较正文。
- 动态事实必须写入 `domain.yml.github_observed`，并更新 `observed_at`。
- `raw/` 保存原始事实层，必须通过 `python3 scripts/fetch-research-raw.py` 刷新。
- 不手工改写 `raw/*.raw.*` 文件；稳定事实摘要再同步到 `domain.yml`。
- README 只写判断、定位、使用方式和后续观察点，不堆外部 README 全文。
- `analysis.md` 写 L1 结构化理解；`deep-dive.md` 写 L2 源码证据、关键机制和可迁移模式。
- 如果需要横向比较，在 `docs/research/README.md` 或新的对比文档中处理，不把本目录重新变成聚合域。
- 修改后运行 `make sync-doc-toc` 和 `make test`。
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# datawhalechina/easy-vibe 研究域
## 字多不看
- 本目录研究 `datawhalechina/easy-vibe` 这个外部仓库。
- 当前优先级：P2；研究角色：中文分阶段交互式课程。
- GitHub 动态事实放在 `domain.yml`，观测日期为 2026-07-03。
## 快速导航
| 文档 | 定位 |
|:---|:---|
| [domain.yml](domain.yml) | 仓库事实快照、研究方向、优先级和来源证据。 |
| [analysis.md](analysis.md) | 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。 |
| [deep-dive.md](deep-dive.md) | L2 源码/结构深度研究、关键机制和可迁移模式。 |
| [AGENTS.md](AGENTS.md) | 本研究域维护规则。 |
<details>
<summary><strong>完整细粒度目录（点击展开/收起）</strong></summary>
### 细粒度目录
- [domain.yml](domain.yml) - 仓库事实快照、研究方向、优先级和来源证据。
- [analysis.md](analysis.md) - 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。
- [deep-dive.md](deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [AGENTS.md](AGENTS.md) - 本研究域维护规则。
</details>
## 使用方式
- 先读本 README 的判断，再读 `analysis.md` 和 `deep-dive.md` 的研究结论，最后读 `domain.yml`。
- 需要引用 stars、forks、release、归档状态时，先重新核验 GitHub。
- 如果形成稳定方法论，再迁入 concepts、references、workflow 或 skills。
## 正文
### 研究定位
`datawhalechina/easy-vibe` 的当前研究定位是：中文分阶段交互式课程。
### 当前判断
适合研究学习地图、交互式教程和现代前端课程包装。
### 观察字段
- GitHub URL：https://github.com/datawhalechina/easy-vibe
- 当前研究方向：`cn-onboarding`
- 当前优先级：P2
- 当前归档状态：`false`
- 主要语言：`JavaScript`
### 后续观察
- 是否有稳定文档结构、命令入口和可复用工作流。
- 是否能反哺本仓库的 concepts、references、workflow 或 skills。
- 是否存在许可证、归档状态、维护活跃度或生态迁移风险。
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# datawhalechina/easy-vibe 研究分析
## 本轮结论
`datawhalechina/easy-vibe` 的核心价值是课程产品化：它不是单篇教程，而是把 Vibe Coding 按用户目标、
学习阶段、站点化文档、AI 可读入口和课程资源组织成可持续学习系统。
本仓最应该迁移的是学习路径分流：新手、原型构建者、全栈产品用户、AI-Native 进阶用户不应该读同一条路径。
但本仓不能直接复制站点结构，应该把它改良成 `getting-started` 的用户身份和产出导向路线。
## 本地证据
- 研究对象：`datawhalechina/easy-vibe`
- 当前研究角色：中文分阶段交互式课程
- 原始仓库：`raw/repository/`
- 原始来源清单：`raw/sources.yml`
- 事实摘要：`domain.yml`
- 深度证据：`deep-dive.md`
## 对标拆解
| 项 | 内容 |
|:---|:---|
| 参考对象 | `datawhalechina/easy-vibe` |
| 它解决的核心问题 | 让不同目标的中文用户知道从哪条路线开始学习 Vibe Coding |
| 核心机制 | `docs/` 课程内容、站点配置、脚本、`AGENTS.md`、`CLAUDE.md`、`llms.txt` |
| 真正带来结果的动作 | 用用户目标分流学习路径，而不是只按技术栈罗列知识 |
| 可迁移做法 | 新手 first win、idea to prototype、full-stack、AI-Native 进阶路径 |
| 不可迁移条件 | 不复制站点工程和大体量课程目录，本仓保持轻量文档知识库 |
| 下一步试用动作 | 重构 `docs/getting-started/learning-map.md` 的用户身份和阶段分流 |
## 改良迭代
| 改良目标 | 原模式 | 本仓版本 | 验证指标 |
|:---|:---|:---|:---|
| 用户分流 | 按学习目标给路线 | 零基础、开发者、创业者、维护者、高阶 Agent 用户 | 用户能在 30 秒内找到路线 |
| 产出导向 | 先给 first win | 每个阶段写清能做出什么 | 路线不再只列文档链接 |
| AI 可读入口 | `AGENTS.md`、`CLAUDE.md`、`llms.txt` | 本仓 `AGENTS.md`、`llms.txt`、`llms-full.txt` 协同 | AI 能按入口读取上下文 |
## 可迁移清单
- 让入门路径先回答“你会做出什么”，再讲概念。
- 按用户身份和目标组织学习地图。
- 在每个阶段写清前置条件、产出、验证方式和下一步。
- 保持 AI 可读入口和人类入口同步。
## 不可迁移清单
- 不把本仓变成大型课程站点。
- 不直接迁移其目录和站点构建方式。
- 不把课程包装等同于工程治理。
## 验证动作
| 动作 | 成功信号 | 失败信号 |
|:---|:---|:---|
| 抽样重写一个 getting-started 路线 | 用户能按身份选择路径 | 所有人仍读同一条线 |
| 给每阶段补产出和验证 | 每阶段有可见成果 | 仍只是资料链接 |
| 检查 AI 入口同步 | llms 和 README 指向一致 | AI 入口缺最新路径 |
## 沉淀判断
- 稳定结论进入 `docs/getting-started/` 和 `docs/README.md`。
- 本研究域保持 P2 教程产品化对标对象。
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# datawhalechina/easy-vibe 深度研究
## 研究级别
- 当前级别：L2 源码/结构深度研究。
- 研究对象：`datawhalechina/easy-vibe`。
- 证据来源：本目录 `raw/` 下的 GitHub 元数据、README 快照和本地仓库工作树。
- 观察日期：2026-07-03。
## L2 结论
`datawhalechina/easy-vibe` 是课程站点化最强的中文 Vibe Coding 对标对象。它不是简单 Markdown
教程，而是用 VitePress、多语言目录、交互式组件、站点部署脚本、`llms.txt`、`AGENTS.md` 和
`CLAUDE.md` 把课程包装成面向人类和 AI 的学习产品。
对本仓最有价值的点不是复制它的站点复杂度，而是学习它如何把“零基础学习路径”拆成用户目标、
学习阶段、视觉演示、交互组件和 AI 可读入口。
## 源码证据
- `raw/repository/README.md`：主叙事入口，包含学习路径、多语言入口、在线阅读和本地运行说明。
- `raw/repository/docs/`：VitePress 文档主体。
- `raw/repository/docs-readme/`：多语言 README 入口。
- `raw/repository/docs/zh-cn/index.md`：中文内容入口。
- `raw/repository/docs/en/index.md`：英文内容入口。
- `raw/repository/docs/public/llms.txt`：站点级 AI 读取入口。
- `raw/repository/llms.txt`：仓库级 AI 读取入口。
- `raw/repository/AGENTS.md`：Agent 操作入口。
- `raw/repository/CLAUDE.md`：Claude 入口。
- `raw/repository/docs/.vitepress/config.mjs`：站点配置、多语言和部署环境逻辑。
- `raw/repository/scripts/build-locales.mjs`：多语言构建脚本。
- `raw/repository/scripts/generate-sitemap.mjs`：站点 sitemap 生成脚本。
- `raw/repository/package.json`：VitePress、Vue、Element Plus、Mermaid、Reveal.js 等站点依赖和命令。
## 关键机制
### 学习路径按用户目标组织
Easy Vibe 的 README 把读者导向不同路径，而不是只按技术章节线性排列。它面向的是“我是谁、
我想做什么、应该从哪开始”的 onboarding 问题。这比纯目录更适合零基础和跨背景读者。
### 课程站点和 AI 入口并存
仓库同时保留 VitePress 站点、`llms.txt`、`AGENTS.md` 和 `CLAUDE.md`。这说明成熟教程需要同时
服务三类读取者：浏览器用户、搜索引擎/AI 引用系统、AI Agent。
### 多语言是产品能力，不是翻译附件
`docs-readme/`、多语言目录和 `config.mjs` 中的 locale 配置说明，多语言不是附属文件，而是站点
路由、构建、SEO 和内容维护的一部分。多语言会显著提升触达，但也显著提高维护成本。
### 交互式解释降低新手门槛
assets 中的 IDE、RAG、terminal、diffusion 等视觉材料说明，零基础教程不能只靠概念解释。
可视化和交互式组件能把抽象工程概念变成可感知流程。
## 可迁移模式
- 本仓 getting-started 应按“用户身份 + 目标产出 + 当前阶段”重组入口，而不只按知识分类。
- 对关键教程增加“你将做出什么”“需要什么前置条件”“卡住怎么验证”。
- `llms.txt` 和 `assets/ai-citation/llms-full.txt` 应继续作为 AI 入口维护，而不是事后补充。
- 如果未来站点化，应先保留轻量结构，避免过早引入多语言构建复杂度。
- 对 RAG、terminal、Git、IDE、agent 等抽象主题增加可视化解释或最小交互示例。
## 对本仓的影响
本仓当前优势是治理、研究域、资源和质量门禁；Easy Vibe 的优势是课程产品化和新手体验。
两者结合后，本仓可形成两层入口：
- `getting-started/`：面向新手的目标导向学习路径。
- `references/`、`workflow/`、`research/`：面向进阶用户和维护者的工程治理层。
关键取舍是：吸收学习路径和 AI 入口设计，不复制完整多语言站点复杂度。
## 风险和待验证项
- 多语言和站点组件会显著增加维护成本，本仓不能为了展示效果牺牲文档治理稳定性。
- 本轮没有运行 Easy Vibe 的构建、测试和多语言脚本。
- 站点视觉资产丰富，但不等同于工程治理成熟度。
## 下一步 L3 验证任务
- 对照 Easy Vibe 的学习路径，重审本仓 `docs/getting-started/` 是否按用户目标组织。
- 为本仓补一个“零基础到第一个可部署产物”的路径表。
- 抽取 AI 入口设计经验，更新 `llms.txt` / `llms-full.txt` 维护规则。
- 评估是否需要为关键概念增加图片、流程图或交互式示例。
docs/research/datawhalechina-easy-vibe/domain.yml
-52
View File
@@ -1,52 +0,0 @@
version: 1
repo:
name: datawhalechina/easy-vibe
source_name: datawhalechina/easy-vibe
url: https://github.com/datawhalechina/easy-vibe
research:
domain_id: datawhalechina-easy-vibe
domain_name: datawhalechina/easy-vibe 研究域
primary_direction: cn-onboarding
role: 中文分阶段交互式课程
priority: 2
why_study: 适合研究学习地图、交互式教程和现代前端课程包装。
github_observed:
observed_at: '2026-07-03'
source: gh repo view
stars: 17686
forks: 1673
archived: false
language: JavaScript
license: null
default_branch: main
pushed_at: '2026-06-17T01:53:13Z'
updated_at: '2026-07-02T21:29:04Z'
latest_release: null
homepage: https://datawhalechina.github.io/easy-vibe/
topics:
- ai
- course
- vibe-coding
- coding
- genai
- low-code
- no-code
- programming
- tutorial
- vibecoding
- vscode
- agent
- gemini
- gpt
- llm
- nextjs
- openai
- workflow
- mcp
- deepseek
source_evidence:
file: ChatGPT-中文Vibe Coding仓库 (2).md
line: 26
maintenance:
fact_policy: GitHub 动态字段只代表 observed_at 当日快照，更新结论前必须重新核验。
split_policy: 本目录已经是一等研究域；更深分析放入本目录新增文档。
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# raw/ Agent 指南
本目录是 `datawhalechina/easy-vibe` 的原始事实层。
## 维护规则
- 只保存从研究对象拉取的一手材料，不写分析判断。
- `repository/` 是本地 Git 工作树，刷新时由脚本 clone 或 fast-forward pull。
- 不手工改写 `*.raw.*` 文件内容；需要刷新时运行 `python3 scripts/fetch-research-raw.py`。
- `sources.yml` 必须记录拉取时间、来源命令和每个文件的状态。
- 外部 README 原文必须保存为 `.txt`，避免本仓库 Markdown 链接检查误判。
- 分析、判断、采用建议和沉淀路径写回上一级 `README.md`、`analysis.md` 或 `decisions.md`。
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# raw 事实层
本目录保存 `datawhalechina/easy-vibe` 的本地原始材料快照。
这里不写分析结论，只保存可复查的一手资料：
- `sources.yml`：来源清单、拉取时间、命令和文件状态。
- `repository/`：Git 仓库工作树；本目录由 `.gitignore` 忽略，只作为本地研究材料。
- `github-repo.raw.json`：GitHub 仓库元数据。
- `github-readme.raw.md.txt`：GitHub README 原文快照。
- `github-license.raw.txt`：GitHub license 原文快照；仓库无 license 时可能不存在。
- `github-root-contents.raw.json`：默认分支根目录内容快照。
- `github-languages.raw.json`：GitHub language 统计快照。
- `github-latest-release.raw.json`：最新 release 快照；无 release 时可能不存在。
`repository/` 是外部源码快照，不参与本仓库 Markdown、链接、README/AGENTS 覆盖检查。原始 README 使用 `.txt` 后缀保存，避免其中的外部相对链接被本仓库 Markdown 链接检查误判。
docs/research/datawhalechina-easy-vibe/raw/github-languages.raw.json
-5
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@@ -1,5 +0,0 @@
{
"JavaScript": 17384,
"Dockerfile": 774,
"Shell": 502
}
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<!-- trigger vercel build -->
<div align="center">
<img src="assets/easy-vibe-logo-hd.svg" alt="Easy-Vibe Logo" width="300">
<img src="assets/banner.png" alt="Easy-Vibe Banner" width="100%">
<p align="center" style="font-size: 1.2em; color: #666; margin: 20px 0;">
Jump right in and vibe together — if you can talk, you can build apps.<br>
<span style="font-size: 0.9em; color: #888;">直接上手，一起 vibe！会说话就会做应用。</span>
</p>
<a href="https://trendshift.io/repositories/22079" target="_blank"><img src="https://trendshift.io/api/badge/repositories/22079" alt="datawhalechina/easy-vibe | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
<p align="center" style="font-size: 1.05em; color: #666; margin: 16px 0;">
你好 · Hello · 哈囉 · こんにちは · 안녕하세요 · Hola · Bonjour · Hallo · مرحبا · Xin chào<br>
Our tutorial supports 10 languages. Let's code together!<br>
<span style="font-size: 0.9em; color: #888;">我们的教程支持 10 种语言，欢迎世界各地的朋友一起 coding！</span>
</p>
<p align="center">
🚀 <a href="https://datawhalechina.github.io/easy-vibe/welcome.html">Start Exploring</a> · ✨ <a href="https://datawhalechina.github.io/easy-vibe/en/appendix/">Interactive Tutorial</a> · 🦞 <a href="https://github.com/datawhalechina/hello-claw">Learn OpenClaw</a> · 📖 <a href="#table-of-contents">Table of Contents</a><br>
<span style="font-size: 0.85em; color: #888;">🚀 <a href="https://datawhalechina.github.io/easy-vibe/welcome.html">开始体验</a> · ✨ <a href="https://datawhalechina.github.io/easy-vibe/zh-cn/appendix/">交互式教程</a> · 🦞 <a href="https://github.com/datawhalechina/hello-claw">学习 OpenClaw</a> · 📖 <a href="#table-of-contents">查看目录</a></span>
</p>
<p align="center">
<a href="https://datawhalechina.github.io/easy-vibe/welcome.html">Read Online</a> ·
<a href="#-content-navigation">Learning Map</a><br>
<span style="font-size: 0.85em; color: #888;">
<a href="https://datawhalechina.github.io/easy-vibe/welcome.html">开始阅读</a> ·
<a href="#-content-navigation">学习地图</a>
</span>
</p>
<p align="center">
<a href="https://github.com/datawhalechina/easy-vibe/stargazers" target="_blank">
<img src="https://img.shields.io/github/stars/datawhalechina/easy-vibe?color=660874&style=for-the-badge&logo=star&logoColor=white&labelColor=1a1a2e" alt="Stars"></a>
<a href="https://github.com/datawhalechina/easy-vibe/network/members" target="_blank">
<img src="https://img.shields.io/github/forks/datawhalechina/easy-vibe?color=660874&style=for-the-badge&logo=git-fork&logoColor=white&labelColor=1a1a2e" alt="Forks"></a>
<a href="LICENSE" target="_blank">
<img src="https://img.shields.io/badge/License-CC_BY_NC_SA_4.0-4ecdc4?style=for-the-badge&logo=creative-commons&logoColor=white&labelColor=1a1a2e" alt="License"></a>
</p>
<p align="center">
<a href="README.md"><img alt="English" src="https://img.shields.io/badge/English-d9d9d9"></a>
<a href="docs-readme/zh-CN/README.md"><img alt="简体中文" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
<a href="docs-readme/zh-TW/README.md"><img alt="繁體中文" src="https://img.shields.io/badge/繁體中文-d9d9d9"></a>
<a href="docs-readme/ja-JP/README.md"><img alt="日本語" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
<a href="docs-readme/es-ES/README.md"><img alt="Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
<a href="docs-readme/fr-FR/README.md"><img alt="Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
<a href="docs-readme/ko-KR/README.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
<a href="docs-readme/ar-SA/README.md"><img alt="العربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
<a href="docs-readme/vi-VN/README.md"><img alt="Tiếng_Việt" src="https://img.shields.io/badge/Tiếng_Việt-d9d9d9"></a>
<a href="docs-readme/de-DE/README.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-d9d9d9"></a>
</p>
</div>
<table align="center">
<tr>
<td width="50%" valign="top" align="center">
<img src="assets/gif-header.png" width="100%">
<br>
<strong>A beginner-friendly learning map</strong>
<br>
<sub>Clear guidance from zero, so you can stop "learning and forgetting"</sub>
</td>
<td width="50%" valign="top" align="center">
<img src="assets/gif-tutorial.png" width="100%">
<br>
<strong>Step-by-step visual tutorials</strong>
<br>
<sub>Detailed walkthroughs that feel like learning with a private tutor</sub>
</td>
</tr>
<tr>
<td width="50%" valign="top" align="center">
<img src="assets/gif-ide.gif" width="100%">
<br>
<strong>Immersive simulated coding</strong>
<br>
<sub>Virtual mouse guidance helps you quickly learn the core IDE workflow</sub>
</td>
<td width="50%" valign="top" align="center">
<img src="assets/gif-diffusion.gif" width="100%">
<br>
<strong>Visible AI principles</strong>
<br>
<sub>Animated explanations make it easy to see how AI generates images</sub>
</td>
</tr>
<tr>
<td width="50%" valign="top" align="center">
<img src="assets/gif-rag.gif" width="100%">
<br>
<strong>Learn RAG like a game</strong>
<br>
<sub>Interactive components let you click through the full RAG data flow</sub>
</td>
<td width="50%" valign="top" align="center">
<img src="assets/git-terminal.gif" width="100%">
<br>
<strong>Visual terminal concepts</strong>
<br>
<sub>Command-line behavior becomes intuitive when the underlying logic is visualized</sub>
</td>
</tr>
</table>
<div align="center">
<h3>⭐ <a href="https://github.com/datawhalechina/easy-vibe" style="color: #d0cd16ff;">Star the repo here</a> to help accelerate updates ❤️</h3>
</div>
<div align="center" style="margin: 30px 0;">
<a href="https://github.com/datawhalechina/easy-vibe/issues/new?template=story_submission.md">
<img src="https://raw.githubusercontent.com/datawhalechina/easy-vibe/main/assets/stories_image.png" alt="Share Your Vibe Story" width="80%" style="border-radius: 10px; box-shadow: 0 4px 12px rgba(0,0,0,0.15);">
</a>
<p style="margin-top: 15px; font-size: 1.1em; color: #666;">
📝 <strong>Have your own vibe coding story?</strong>
Submit it here and inspire others!
</p>
</div>
## Table of Contents
- [Why Easy-Vibe](#why-easy-vibe)
- [News](#-news)
- [Who This Is For](#who-this-is-for)
- [Your Learning Paths](#your-learning-paths)
- [Study Suggestions](#study-suggestions)
- [I. Beginner Entry](#i-beginner-entry)
- [II. Junior and Mid-Level Developers](#ii-junior-and-mid-level-developers)
- [III. Advanced Developers](#iii-advanced-developers)
- [Appendix Knowledge Base](#-appendix-knowledge-base)
- [How To Learn](#️-how-to-learn)
- [Run Locally](#-run-locally)
- [Other Courses](#other-courses)
- [Contributing & Contributors](#-contributing--contributors)
- [LICENSE](#-license)
## Why Easy-Vibe
Want an expense tracker? Say it.
Need a booking system with WeChat login? Say it.
Want a blog with comments? Say it.
In the AI era, programming starts by describing what you want.
Easy-Vibe teaches you how to turn that into a real product.
## 🔥 News
- **[2026-06-17]** 🌍 **Full multilingual coverage complete**: All tutorial content (Stages 1-3) is now available in 10 languages (zh-cn, en, zh-tw, ja-jp, ko-kr, es-es, fr-fr, de-de, ar-sa, vi-vn), covering product prototyping, full-stack development, and cross-platform development.
- **[2026-03-29]** ✨ **Vibe Stories launched and upgraded with real user journeys**: Added a new homepage Vibe Stories section with an interactive carousel and dedicated story pages, then replaced placeholder content with four real user stories featuring a rural primary school teacher, a college student, a high school IT teacher, and a truck driver who built real products with AI. [👉 View the stories](https://datawhalechina.github.io/easy-vibe/zh-cn/vibe-stories/story-1.html)
- **[2026-03-26]** 🚀 **Major Stage 2 practice update**: Completed the SaaS capstone project "[Your First SaaS Full-Stack App: Copywriting Generator Website](https://datawhalechina.github.io/easy-vibe/en/stage-2/assignments/fullstack-app/)" and substantially expanded the "[How to integrate Stripe and payment systems](https://datawhalechina.github.io/easy-vibe/en/stage-2/backend/stripe-payment/)" section, plus key content around multi-product UI and WeChat Mini Program backend workflows.
- **[2026-03-25]** 📚 **New appendix: User Research and Requirement Validation**: Added four new articles covering idea sourcing, the Double Diamond model, Jobs to Be Done, and The Mom Test to help beginners discover and validate product ideas. [👉 Read the appendix](https://datawhalechina.github.io/easy-vibe/en/appendix/)
- **[2026-03-25]** 📚 **English documentation fully updated**: Stage 2 (Full-stack Development) and Stage 3 (Advanced Development) are now fully available in English. [👉 Start learning](https://datawhalechina.github.io/easy-vibe/en/stage-2/)
<details>
<summary>Past News</summary>
- **[2026-03-02]** 🦞 **OpenClaw and AI Agent friendly support**: Added `llms.txt` so OpenClaw, Claude, Cursor, Trae, and other AI agents can quickly understand the repository structure and find the right tutorial content.
- **[2026-03-01]** The [Advanced Development section](https://datawhalechina.github.io/easy-vibe/en/stage-3/) has been comprehensively upgraded with deep guides for Claude Code, including MCP, Skills, Agent Teams, and more, along with eight cross-platform project tutorials.
- **[2026-02-25]** Updated the [Appendix Knowledge Base](https://datawhalechina.github.io/easy-vibe/en/appendix/), now covering 9 knowledge areas and 80+ interactive topics.
- **[2026-01-27]** Added Android and iOS app development tutorials.
- **[2026-01-19]** Released interactive demos for Prompt Engineering, AI history, authentication design, Git principles, and more.
- **[2026-01-16]** Reorganized the project structure and formally established a beginner entry path.
- **[2026-01-14]** Completed a large update to the Stage 1 product prototyping docs.
- **[2026-01-13]** Refactored the documentation architecture and fully enabled multi-language support.
- **[2026-01-01]** Released the core learning map for the project.
</details>
## Who This Is For
- **Complete beginners**: Build your first project first, then understand how it works
- **Product managers / founders**: Validate ideas fast and build MVPs at low cost
- **Students**: Develop practical skills for the AI era
- **Junior developers**: Learn the full path from idea to launch
- **Mid-level and senior developers**: Upgrade your AI collaboration workflow for complex projects
## Your Learning Paths
### 🎮 I want a fast first win
**Best for**: Everyone
**What you will learn**: What AI coding actually feels like through a simple, concrete hands-on example
**What you will get**: A clear first impression of vibe coding and how to work with AI by conversation
[Start here](https://datawhalechina.github.io/easy-vibe/en/stage-1/ai-capabilities-through-games/)
### 💡 I want to turn an idea into a product prototype
**Best for**: Beginners / product managers / founders
**What you will learn**: Learning roadmap, AI IDE tools, idea validation, prototyping, AI capability integration, and full demo iteration
**What you will get**: A demoable AI product prototype you can actually show to users or teammates
[Start learning](https://datawhalechina.github.io/easy-vibe/en/stage-1/learning-map/)
### 🚀 I want to build full-stack products end to end
**Best for**: Junior developers / indie hackers / advanced learners
**What you will learn**: Frontend workflows, design-to-code, databases, backend APIs, deployment, billing, and major projects
**What you will get**: The ability to independently ship modern AI-enabled web applications
[Start learning](https://datawhalechina.github.io/easy-vibe/en/stage-2/)
### AI-Native: I want advanced Claude Code and agent workflows
**Best for**: Developers interested in AI-native engineering
**What you will learn**: Claude Code, MCP, Skills, Agent Teams, long-running tasks, Spec Coding, and cross-platform app delivery
**What you will get**: A stronger workflow for complex AI-assisted development and automation
[Go to advanced development](https://datawhalechina.github.io/easy-vibe/en/stage-3/)
### 📚 I want reference material and fundamentals
**Best for**: Everyone
**What you will learn**: Computer fundamentals, frontend/backend basics, infrastructure, AI principles, and engineering practices
**What you will get**: A long-term reference knowledge base covering 9 major knowledge areas
[Browse the knowledge base](https://datawhalechina.github.io/easy-vibe/en/appendix/)
## Study Suggestions
- If you are a beginner, product manager, or founder, start with [Stage 1](https://datawhalechina.github.io/easy-vibe/en/stage-1/learning-map/)
- If you want to move from prototypes to full-stack delivery, start with [Stage 2](https://datawhalechina.github.io/easy-vibe/en/stage-2/)
- If you want advanced Claude Code workflows or cross-platform projects, go to [Stage 3](https://datawhalechina.github.io/easy-vibe/en/stage-3/)
- If you get blocked by concepts or missing background knowledge, use the [Appendix Knowledge Base](https://datawhalechina.github.io/easy-vibe/en/appendix/)
### 📖 Content Navigation
<div align="center">
<img src="assets/readme-image1.png" alt="Learning Map" width="70%" style="border-radius: 10px; box-shadow: 0 8px 20px rgba(45,55,72,0.3); margin: 15px 0;"/>
</div>
### I. Beginner Entry
| Section | Key Content |
| :------ | :---------- |
| [Learning Map](https://datawhalechina.github.io/easy-vibe/en/stage-1/learning-map/) | A guided overview of the full learning journey |
| [AI Era: If You Can Speak, You Can Code](https://datawhalechina.github.io/easy-vibe/en/stage-1/ai-capabilities-through-games/) | Get your first feel for AI coding through examples like Snake |
| [Master AI Programming Tools](https://datawhalechina.github.io/easy-vibe/en/stage-1/introduction-to-ai-ide/) | Learn how AI IDE tools work and build simple local projects with them |
| [Find Great Ideas](https://datawhalechina.github.io/easy-vibe/en/stage-1/finding-great-idea/) | Learn how to discover and validate product ideas worth building |
| [Build Product Prototypes](https://datawhalechina.github.io/easy-vibe/en/stage-1/building-prototype/) | Move from requirements to single-page and multi-page product prototypes |
| [Integrate AI Capabilities](https://datawhalechina.github.io/easy-vibe/en/stage-1/integrating-ai-capabilities/) | Integrate text, image, and video AI features |
| [Complete project practice](https://datawhalechina.github.io/easy-vibe/en/stage-1/complete-project-practice/) | Simulate real scenarios, collect user feedback, and iterate on a full project |
#### Appendix: Product and Business Thinking
| Section | Key Content |
| :------ | :---------- |
| [Product Thinking and Solution Design](https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-a-product-thinking/) | Core frameworks for going from zero to one with a product |
| [AI Industry Application Scenarios (B-end)](https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-industry-scenarios/) | Understand how AI is applied across industries |
| [AI Consumer Scenarios Inspiration (C-end)](https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-c-consumer-scenarios/) | Explore product opportunities in consumer AI |
#### Appendix: User Research and Requirement Validation
| Section | Key Content |
| :------ | :---------- |
| [Where to find ideas: 3 reference sources that work best for beginners](https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-idea-sources/) | Build a reliable pipeline for finding concrete product opportunities |
| [Double Diamond: first do the right thing, then do it right](https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-double-diamond/) | Use a structured process to move from scattered inspiration to a workable direction |
| [Use Jobs to Be Done to find what users really want done](https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-jobs-to-be-done/) | Analyze user goals through real tasks instead of surface-level feature requests |
| [The Mom Test: a user interview method for validating demand](https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-mom-test/) | Learn how to ask better questions and avoid false-positive feedback |
#### Appendix: Technical Solutions
| Section | Key Content |
| :------ | :---------- |
| [What to do if you encounter errors](https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-b-common-errors/) | Common vibe coding issues and how to troubleshoot them |
| [Comparison of Seven AI Programming Tools](https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-articles/example0-1/vibe-coding-tools-snake-game-tutorial) | Compare major AI coding platforms through hands-on testing |
| [Design Websites with Agents](https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-articles/example0-2/vibe-coding-tools-build-website-with-ai-coding-and-design-agents) | Learn multi-agent collaboration in practice |
### II. Junior and Mid-Level Developers
#### Frontend
| Section | Key Content |
| :------ | :---------- |
| [Frontend 0: Build Your Own Asset-Production Agent with Lovart](https://datawhalechina.github.io/easy-vibe/en/stage-2/frontend/lovart-assets/) | Use Nanobanana and Lovart to batch-generate visual assets and build a drawing agent with intent recognition |
| [Frontend 1: Figma & MasterGo Basics](https://datawhalechina.github.io/easy-vibe/en/stage-2/frontend/figma-mastergo/) | Learn the workflow from design drafts to implementation-ready UI thinking |
| [Frontend 2: Build Your First Modern App - UI Design](https://datawhalechina.github.io/easy-vibe/en/stage-2/frontend/ui-design/) | Learn the UI design foundations behind modern application interfaces |
| [Frontend 3: UI Guidelines and Multi-Product Design](https://datawhalechina.github.io/easy-vibe/en/stage-2/frontend/multi-product-ui/) | Improve consistency and aesthetics across multiple products with shared UI rules |
| [Frontend 4: Make Interfaces Beautiful with LLMs and Skills](https://datawhalechina.github.io/easy-vibe/en/stage-2/frontend/llm-skills-beautiful/) | Use prompts and plugins to make AI generate more polished, distinctive interfaces |
| [Frontend 4: Let's Build Hogwarts Portraits](https://datawhalechina.github.io/easy-vibe/en/stage-2/frontend/hogwarts-portraits/) | Build an interactive AI-image frontend project from scratch |
| [Frontend 6: From Design Prototype to Project Code](https://datawhalechina.github.io/easy-vibe/en/stage-2/frontend/design-to-code/) | Turn design prototypes into frontend code that can really run in the browser |
| [Frontend 7: Upgrade Your UI with Modern Component Libraries](https://datawhalechina.github.io/easy-vibe/en/stage-2/frontend/modern-component-library/) | Use component libraries to build professional interfaces faster |
#### Backend
| Section | Key Content |
| :------ | :---------- |
| [Backend 1: Learn Git and GitHub](https://datawhalechina.github.io/easy-vibe/en/stage-2/backend/git-workflow/) | Master core version control operations and collaboration workflows with Git |
| [Backend 2: From Database to Supabase](https://datawhalechina.github.io/easy-vibe/en/stage-2/backend/database-supabase/) | Learn relational database basics and use Supabase as a modern BaaS platform |
| [Backend 3: Backend API Design and Development](https://datawhalechina.github.io/easy-vibe/en/stage-2/backend/ai-interface-code/) | Use AI to assist API design, backend code generation, and API documentation |
| [Backend 4: Ship Your Product Prototype](https://datawhalechina.github.io/easy-vibe/en/stage-2/backend/zeabur-deployment/) | Quickly deploy full-stack applications to the cloud with Zeabur |
| [Backend 5: From IDEs to CLI AI Coding Tools](https://datawhalechina.github.io/easy-vibe/en/stage-2/backend/modern-cli/) | Explore terminal-first AI coding workflows for modern development |
| [Backend 6: Integrate Stripe and Other Billing Systems](https://datawhalechina.github.io/easy-vibe/en/stage-2/backend/stripe-payment/) | Add monetization with payment and billing capabilities |
#### Major Projects
| Section | Key Content |
| :------ | :---------- |
| [Major Project 1: Your First SaaS Full-Stack App - AI Copywriting Website](https://datawhalechina.github.io/easy-vibe/en/stage-2/assignments/fullstack-app/) | Build an AI marketing copy workspace with login, generation, billing, and admin management |
| [Major Project 2: Online Exam and Management System](https://datawhalechina.github.io/easy-vibe/en/stage-2/assignments/modern-frontend-trae/) | Build an online exam system with question generation, test-taking flows, and admin tools |
#### AI Capabilities Appendix
| Section | Key Content |
| :------ | :---------- |
| [AI 1: Dify Basics & Knowledge Base Integration](https://datawhalechina.github.io/easy-vibe/en/stage-2/ai-capabilities/dify-knowledge-base/) | Learn to build AI applications with Dify and integrate private knowledge bases |
### III. Advanced Developers
#### Claude Code Core Skills
| Section | Key Content |
| :------ | :---------- |
| [Getting started with Claude Code](https://datawhalechina.github.io/easy-vibe/en/stage-3/core-skills/basics/) | Installation, setup, fundamentals, and useful commands |
| [Claude Code MCP guide](https://datawhalechina.github.io/easy-vibe/en/stage-3/core-skills/mcp/) | Connect Claude Code to GitHub, databases, APIs, and other services through MCP |
| [Claude Code Skills guide](https://datawhalechina.github.io/easy-vibe/en/stage-3/core-skills/skills/) | Package expertise into reusable skills you can use again and again |
| [How to keep Claude Code working for long-running tasks](https://datawhalechina.github.io/easy-vibe/en/stage-3/core-skills/long-running-tasks/) | Design long-running tasks so coding tools can keep working until the job is done |
| [Claude Agent Teams guide](https://datawhalechina.github.io/easy-vibe/en/stage-3/core-skills/agent-teams/) | Coordinate multiple AI instances like a real development team |
| [Claude Code Superpowers for engineering-grade development](https://datawhalechina.github.io/easy-vibe/en/stage-3/core-skills/superpowers/) | Help AI produce engineering-grade code with TDD and best practices |
| [Claude Code workflow best practices](https://datawhalechina.github.io/easy-vibe/en/stage-3/core-skills/workflow/) | Best practices for refactoring, code review, and daily development |
| [Claude Code remote development on mobile](https://datawhalechina.github.io/easy-vibe/en/stage-3/core-skills/mobile-development/) | Use Claude Code beyond the desktop and build a productive remote workflow on mobile devices |
| [Claude Agent SDK complete guide](https://datawhalechina.github.io/easy-vibe/en/stage-3/core-skills/claude-agent-sdk/) | Build custom agent workflows and integrate Claude into your own tools with the SDK |
| [From vibe coding to spec coding](https://datawhalechina.github.io/easy-vibe/en/stage-3/core-skills/spec-coding/) | Move from ad-hoc prompting to a more structured, specification-driven AI development workflow |
#### Cross-Platform Development
| Section | Key Content |
| :------ | :---------- |
| [How to choose the right platform for your app](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/choose-platform/) | Compare app forms and choose the right platform based on users, scenarios, and delivery goals |
| [Build a WeChat Mini Program](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/wechat-miniprogram/) | Understand the ecosystem and ship a frontend mini program from template to launch |
| [Build a WeChat Mini Program with backend](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/wechat-miniprogram-backend/) | Add backend logic and databases to complete the full business loop |
| [Build an Android app](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/android-app/) | Learn Android app development with a modern native workflow |
| [Build an iOS app](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/ios-app/) | Learn iOS app development and the conventions of the Apple ecosystem |
| [Build a local PWA app](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/pwa-local-app/) | Turn a website into a real app with offline support, push, and installation |
| [Build a browser AI assistant extension](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/browser-ai-extension/) | Create a Chrome extension that summarizes any page with either cloud APIs or built-in AI |
| [Build an Electron desktop app](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/electron-voice-to-text/) | Build a voice-to-text desktop app with Electron for three platforms |
| [Rapidly build and mint an NFT](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/nft-minting/) | Write a smart contract from scratch, deploy it, and mint your own NFT |
| [Build a VS Code extension](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/vscode-extension/) | Build an AI project assistant with templates, code chat, and multi-file Q&A |
| [Build an industrial-grade Qt desktop app](https://datawhalechina.github.io/easy-vibe/en/stage-3/cross-platform/qt-industrial-hmi/) | Create a real-time Qt HMI system with trends, alerts, and monitoring |
#### AI Capabilities Appendix
| Section | Key Content |
| :------ | :---------- |
| [What is RAG and how does it work](https://datawhalechina.github.io/easy-vibe/en/stage-3/ai-advanced/rag-introduction/) | Build a systematic understanding of RAG principles and common architectures |
| [Intermediate and advanced RAG workflows with LangGraph](https://datawhalechina.github.io/easy-vibe/en/stage-3/ai-advanced/langgraph-advanced-rag/) | Design multi-step workflows and more advanced RAG systems |
### 📚 Appendix Knowledge Base
> Covering **9 major knowledge areas** and **80+ interactive topics**, this appendix uses animation and visual components to help you intuitively understand core concepts from computer fundamentals to the AI frontier.
>
> 👉 [View the full appendix](https://datawhalechina.github.io/easy-vibe/en/appendix/)
### 🎓 Other Courses
- [Hands-on Modern RL](#other-courses)
- [Learn Harness Engineering](#other-courses)
## 🛠️ How To Learn
- Read and practice the sections that match your current level. If you get stuck, feel free to open an issue.
## 💻 Run Locally
### Modern approach
In an AI IDE chat window such as VS Code, Cursor, or Trae, you can simply say:
```text
Please help me run this project locally.
```
### Traditional approach
1. `npm install`
2. `npm run dev`
3. Open `http://localhost:3000` in your browser.
## Other Courses
Our team has also created other courses! Check them out:
[![Hands-on Modern RL](https://img.shields.io/badge/HANDS--ON_MODERN_RL-0052cc?style=for-the-badge)](https://github.com/walkinglabs/hands-on-modern-rl)
**Hands-on Modern RL**: An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.
[![Learn Harness Engineering](https://img.shields.io/badge/LEARN_HARNESS_ENGINEERING-0052cc?style=for-the-badge)](https://github.com/walkinglabs/learn-harness-engineering/tree/main)
**Learn Harness Engineering**: A comprehensive guide to harness engineering.
## 🤝 Contributing & Contributors
- If you find an issue or see something that can be improved, feel free to open an issue. If nobody replies, you can also contact the [Datawhale support team](https://github.com/datawhalechina/DOPMC/blob/main/OP.md).
- If you want to contribute, open a pull request. If nobody replies, you can also contact the [Datawhale support team](https://github.com/datawhalechina/DOPMC/blob/main/OP.md).
- If you want to start a new Datawhale open-source project, please follow the [Datawhale Open Source Project Guide](https://github.com/datawhalechina/DOPMC/blob/main/GUIDE.md).
### 🙏 Contributors
- [Sanbu - Project Lead](https://github.com/sanbuphy) (Datawhale member)
- Fang Ke - Mentor (Datawhale member, Tsinghua University)
- [Yerim Kang](https://github.com/yerim25) (Practice projects, Tsinghua University)
- [Zhilin Zhao](https://github.com/ChileenZ) (Practice projects, Tsinghua University)
- [Yixuan Li](https://yixuan20.github.io/) (Visual design, Tsinghua University)
- Siyi Liu (Practice projects, Tsinghua University)
- [Lixin Liu](https://github.com/liulx25xx) (Practice projects, Tsinghua University)
- Everyone in the AI Vibe Coding 101 internal testing group who shared suggestions and feedback
### Special Thanks
- Thanks to [@Sm1les](https://github.com/Sm1les) for the help and support on this project
- Thanks to every contributor and everyone who supported the project with feedback and stars ❤️
<div align="center">
<a href="https://www.star-history.com/#datawhalechina/easy-vibe&type=timeline&legend=top-left">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=datawhalechina/easy-vibe&type=timeline&theme=dark&legend=top-left" />
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</picture>
</a>
</div>
<div align=center style="margin-top: 30px;">
<a href="https://github.com/datawhalechina/easy-vibe/graphs/contributors">
<img src="https://contrib.rocks/image?repo=datawhalechina/easy-vibe" />
</a>
</div>
## 📄 LICENSE
<div align="center">
<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/">
<img
alt="Creative Commons License"
style="border-width:0"
src="https://img.shields.io/badge/license-CC%20BY--NC--SA%204.0-lightgrey"
/>
</a>
<br />
This work is licensed under the
<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/">
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
</a>.
</div>
## Star History
[![Star History Chart](https://api.star-history.com/svg?repos=datawhalechina/easy-vibe&type=date&legend=top-left)](https://www.star-history.com/#datawhalechina/easy-vibe&type=date&legend=top-left)
docs/research/datawhalechina-easy-vibe/raw/github-repo.raw.json
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docs/research/datawhalechina-easy-vibe/raw/sources.yml
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version: 1
domain_id: datawhalechina-easy-vibe
object:
type: github_repository
name: datawhalechina/easy-vibe
url: https://github.com/datawhalechina/easy-vibe
pulled_at: '2026-07-02T22:47:14+00:00'
puller: scripts/fetch-research-raw.py
files:
- path: repository/
kind: git-working-tree
status: ok
source: 'git clone --depth=1 --single-branch --no-tags https://github.com/datawhalechina/easy-vibe.git docs/research/datawhalechina-easy-vibe/raw/repository'
- path: github-repo.raw.json
kind: repository-metadata
status: ok
source: 'gh repo view datawhalechina/easy-vibe --json nameWithOwner,url,description,homepageUrl,isArchived,isFork,isMirror,defaultBranchRef,licenseInfo,primaryLanguage,repositoryTopics,stargazerCount,forkCount,watchers,createdAt,updatedAt,pushedAt,latestRelease --jq .'
- path: github-readme.raw.md.txt
kind: readme
status: ok
source: 'gh api repos/datawhalechina/easy-vibe/readme -H Accept: application/vnd.github.raw'
- path: github-license.raw.txt
kind: license
status: missing_or_error
source: 'gh api repos/datawhalechina/easy-vibe/license -H Accept: application/vnd.github.raw'
message: 'gh: Not Found (HTTP 404)'
- path: github-root-contents.raw.json
kind: root-contents
status: ok
source: 'gh api repos/datawhalechina/easy-vibe/contents'
- path: github-languages.raw.json
kind: languages
status: ok
source: 'gh api repos/datawhalechina/easy-vibe/languages'
- path: github-latest-release.raw.json
kind: latest-release
status: missing_or_error
source: 'gh api repos/datawhalechina/easy-vibe/releases/latest'
message: 'gh: Not Found (HTTP 404)'
docs/research/datawhalechina-vibe-vibe/AGENTS.md
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# datawhalechina/vibe-vibe 研究域 Agent 指南
本目录维护 `datawhalechina/vibe-vibe` 的独立研究域。
## 目录职责
```text
datawhalechina-vibe-vibe/
├── README.md # 研究域入口和判断层
├── AGENTS.md # 本目录维护规则
├── domain.yml # 事实摘要层：仓库元数据、研究角色、来源证据
├── analysis.md # L1 结构化研究结论、可借鉴点、风险和下一轮任务
├── deep-dive.md # L2 源码/结构深度研究、关键机制和可迁移模式
└── raw/ # 原始事实层：拉取到本地的一手材料快照
```
## 维护规则
- 本目录只研究 `datawhalechina/vibe-vibe`，不要混入其他仓库的横向比较正文。
- 动态事实必须写入 `domain.yml.github_observed`，并更新 `observed_at`。
- `raw/` 保存原始事实层，必须通过 `python3 scripts/fetch-research-raw.py` 刷新。
- 不手工改写 `raw/*.raw.*` 文件；稳定事实摘要再同步到 `domain.yml`。
- README 只写判断、定位、使用方式和后续观察点，不堆外部 README 全文。
- `analysis.md` 写 L1 结构化理解；`deep-dive.md` 写 L2 源码证据、关键机制和可迁移模式。
- 如果需要横向比较，在 `docs/research/README.md` 或新的对比文档中处理，不把本目录重新变成聚合域。
- 修改后运行 `make sync-doc-toc` 和 `make test`。
docs/research/datawhalechina-vibe-vibe/README.md
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# datawhalechina/vibe-vibe 研究域
## 字多不看
- 本目录研究 `datawhalechina/vibe-vibe` 这个外部仓库。
- 当前优先级：P2；研究角色：中文零基础系统教程。
- GitHub 动态事实放在 `domain.yml`，观测日期为 2026-07-03。
## 快速导航
| 文档 | 定位 |
|:---|:---|
| [domain.yml](domain.yml) | 仓库事实快照、研究方向、优先级和来源证据。 |
| [analysis.md](analysis.md) | 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。 |
| [deep-dive.md](deep-dive.md) | L2 源码/结构深度研究、关键机制和可迁移模式。 |
| [AGENTS.md](AGENTS.md) | 本研究域维护规则。 |
<details>
<summary><strong>完整细粒度目录（点击展开/收起）</strong></summary>
### 细粒度目录
- [domain.yml](domain.yml) - 仓库事实快照、研究方向、优先级和来源证据。
- [analysis.md](analysis.md) - 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。
- [deep-dive.md](deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [AGENTS.md](AGENTS.md) - 本研究域维护规则。
</details>
## 使用方式
- 先读本 README 的判断，再读 `analysis.md` 和 `deep-dive.md` 的研究结论，最后读 `domain.yml`。
- 需要引用 stars、forks、release、归档状态时，先重新核验 GitHub。
- 如果形成稳定方法论，再迁入 concepts、references、workflow 或 skills。
## 正文
### 研究定位
`datawhalechina/vibe-vibe` 的当前研究定位是：中文零基础系统教程。
### 当前判断
适合作为零基础入口，用来观察中文教程如何把 Vibe Coding 讲成可执行路线。
### 观察字段
- GitHub URL：https://github.com/datawhalechina/vibe-vibe
- 当前研究方向：`cn-onboarding`
- 当前优先级：P2
- 当前归档状态：`false`
- 主要语言：`Dockerfile`
### 后续观察
- 是否有稳定文档结构、命令入口和可复用工作流。
- 是否能反哺本仓库的 concepts、references、workflow 或 skills。
- 是否存在许可证、归档状态、维护活跃度或生态迁移风险。
docs/research/datawhalechina-vibe-vibe/analysis.md
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# datawhalechina/vibe-vibe 研究分析
## 本轮结论
`datawhalechina/vibe-vibe` 的核心价值是把零基础 Vibe Coding 讲成“能学、能看、能部署、能演示”的课程。
它用 `docs/`、`demos/`、Docker 和部署说明降低学习门槛，强调从概念走向可见产物。
本仓最应该迁移的是 demo 驱动学习：概念文档必须有验证层，否则用户读完只有认知，没有交付感。
## 本地证据
- 研究对象：`datawhalechina/vibe-vibe`
- 当前研究角色：中文零基础系统教程
- 原始仓库：`raw/repository/`
- 原始来源清单：`raw/sources.yml`
- 事实摘要：`domain.yml`
- 深度证据：`deep-dive.md`
## 对标拆解
| 项 | 内容 |
|:---|:---|
| 参考对象 | `datawhalechina/vibe-vibe` |
| 它解决的核心问题 | 让零基础用户从理解 Vibe Coding 走到运行示例和部署体验 |
| 核心机制 | `docs/` 讲解、`demos/` 示例、Docker 私有化部署、清晰课程定位 |
| 真正带来结果的动作 | 用可运行 demo 把抽象概念落成体验 |
| 可迁移做法 | getting-started 增加最小 demo、部署感和阶段产出 |
| 不可迁移条件 | 不把零基础教程简化为工程标准，不复制课程站点体量 |
| 下一步试用动作 | 为一个核心概念补最小练习或 demo 验证任务 |
## 改良迭代
| 改良目标 | 原模式 | 本仓版本 | 验证指标 |
|:---|:---|:---|:---|
| 概念可验证 | demo 目录承接教程 | concepts 后接 practice / workflow 验证 | 读者能运行或检查一个结果 |
| 部署感 | Docker 私有化部署 | 本仓给出知识库/项目交付的最小上线路径 | 用户知道如何从本地到可访问产物 |
| 零基础解释 | 先讲清概念和体验 | getting-started 降低术语密度 | 非程序员能理解第一步 |
## 可迁移清单
- 每条新手路径至少配一个可验证产物。
- 把 demo / assignment 作为概念验收层。
- 在入门文档里强调“交付感”，不要只讲工具安装。
- 将部署或发布作为早期可选路线。
## 不可迁移清单
- 不把零基础简化表达当作高级工程规范。
- 不复制 Docker/站点结构作为本仓必需能力。
- 不把 demo 数量当作质量。
## 验证动作
| 动作 | 成功信号 | 失败信号 |
|:---|:---|:---|
| 为一个概念补最小练习 | 用户能完成并验证结果 | 练习只是阅读题 |
| 给新手路径补第一个可见产物 | 新手知道第一天做出什么 | 路线仍停在安装工具 |
| 抽样检查 demo 与文档一致 | demo 能解释对应概念 | demo 与正文脱节 |
## 沉淀判断
- 稳定结论进入 `docs/getting-started/`，后续可考虑独立 practice 层。
- 本研究域保持 P2 零基础课程对标对象。
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# datawhalechina/vibe-vibe 深度研究
## 研究级别
- 当前级别：L2 源码/结构深度研究。
- 研究对象：`datawhalechina/vibe-vibe`。
- 证据来源：本目录 `raw/` 下的 GitHub 元数据、README 快照和本地仓库工作树。
- 观察日期：2026-07-03。
## L2 结论
`datawhalechina/vibe-vibe` 是面向零基础用户的系统教程仓库。它的核心不是工具实现，而是把
Vibe Coding 解释成基础篇、进阶篇、实践篇和优质文章篇四层学习路径，并通过 VitePress、demo
项目、Docker 部署和 PWA/SEO 配置把教程做成可访问、可部署、可持续阅读的产品。
对本仓最有价值的是它的课程分层和“从想法到产品”的读者叙事；最需要警惕的是教程产品化很容易
引入站点工程复杂度，偏离本仓作为工程知识库和 Agent 控制面的主轴。
## 源码证据
- `raw/repository/README.md`：中文主入口，定义教程定位、推荐起点、板块和学习产出。
- `raw/repository/README.en.md`：英文入口。
- `raw/repository/docs/Basic/`：基础篇。
- `raw/repository/docs/Advanced/`：进阶篇。
- `raw/repository/docs/Practice/`：实践篇。
- `raw/repository/docs/Articles/`：优质文章篇。
- `raw/repository/demos/`：示例项目入口。
- `raw/repository/demos/demo-01-todo/`：第一个 todo demo。
- `raw/repository/demos/demo-02-todo-auth/`：带认证 demo。
- `raw/repository/demos/demo-03-social-schema/`：schema 练习 demo。
- `raw/repository/docs/deployment/index.md`：部署说明。
- `raw/repository/Dockerfile`：容器化部署入口。
- `raw/repository/docker-compose.yml`：本地私有化部署入口。
- `raw/repository/docs/public/llms.txt`：AI 读取入口。
- `raw/repository/docs/.vitepress/config.mts`：站点、SEO、PWA、FAQ、RSS 和侧边栏配置。
## 关键机制
### 四层课程结构
基础篇解决“能不能开始”，进阶篇解决“能不能完整交付”，实践篇解决“能不能动手练”，文章篇解决
“能不能持续追踪”。这是一种很适合中文用户的学习漏斗。
### Demo 是教程可信度来源
仓库不是只讲理念，还提供 `demos/`。这对零基础教程很关键：读者需要看到具体可运行对象，
否则很容易停在“AI 很厉害”的抽象叙事里。
### 部署能力被前置
README 和 `docs/deployment/index.md` 都强调私有化部署和本地运行。对 Vibe Coding 教程来说，
“能部署给别人看”比“写出代码”更接近真实成就感。
### 站点配置承担传播和检索
`config.mts` 中包含 SEO、RSS、FAQ、PWA、侧边栏和 Mermaid 等能力，说明教程产品化后，传播、
索引和结构导航会成为工程任务。
## 可迁移模式
- 本仓入门路径应明确“基础、进阶、实践、持续追踪”四类入口。
- 每个核心概念最好配一个可运行 demo 或最小任务，而不是只写定义。
- 部署上线应进入入门路径早期，而不是进阶尾部。
- 对面向新手的内容，先写学习产出，再写工具和概念。
- 站点化可以作为未来选项，但本仓当前仍应优先维护 Markdown 可读性和门禁。
## 对本仓的影响
本仓可以吸收 Vibe Vibe 的教程节奏，但要保持自己的差异：
- 本仓更偏工程治理、Agent 协作、研究域和资源治理。
- Vibe Vibe 更偏零基础教育和站点化课程。
- 合理方向是将本仓 getting-started 改得更像“学习路径”，而不是把全仓改成课程站点。
## 风险和待验证项
- 本轮没有运行 VitePress 构建、Docker 部署或 demo 项目。
- 部分 demo 目录可能只是模板或未完成项目，需要逐个验证。
- 面向零基础的表达会有必要简化，不能直接替代本仓进阶工程规范。
## 下一步 L3 验证任务
- 选取 `demos/demo-01-todo/` 作为最小 demo，验证是否可运行。
- 将 Vibe Vibe 的四层课程结构映射到本仓 `getting-started`、`workflow` 和 `references`。
- 为本仓补“学习产出表”：每个阶段读者能做出什么。
- 评估是否需要将部署上线前移到入门路径。
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version: 1
repo:
name: datawhalechina/vibe-vibe
source_name: datawhalechina/vibe-vibe
url: https://github.com/datawhalechina/vibe-vibe
research:
domain_id: datawhalechina-vibe-vibe
domain_name: datawhalechina/vibe-vibe 研究域
primary_direction: cn-onboarding
role: 中文零基础系统教程
priority: 2
why_study: 适合作为零基础入口，用来观察中文教程如何把 Vibe Coding 讲成可执行路线。
github_observed:
observed_at: '2026-07-03'
source: gh repo view
stars: 5633
forks: 445
archived: false
language: Dockerfile
license: null
default_branch: main
pushed_at: '2026-04-30T11:49:58Z'
updated_at: '2026-07-02T17:16:02Z'
latest_release: null
homepage: https://www.vibevibe.cn
topics:
- agent
- agentic-ai
- ai
- coding-assistant
- programming
- vibe-coding
- vibecoding
source_evidence:
file: ChatGPT-中文Vibe Coding仓库 (2).md
line: 25
maintenance:
fact_policy: GitHub 动态字段只代表 observed_at 当日快照，更新结论前必须重新核验。
split_policy: 本目录已经是一等研究域；更深分析放入本目录新增文档。
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# raw/ Agent 指南
本目录是 `datawhalechina/vibe-vibe` 的原始事实层。
## 维护规则
- 只保存从研究对象拉取的一手材料，不写分析判断。
- `repository/` 是本地 Git 工作树，刷新时由脚本 clone 或 fast-forward pull。
- 不手工改写 `*.raw.*` 文件内容；需要刷新时运行 `python3 scripts/fetch-research-raw.py`。
- `sources.yml` 必须记录拉取时间、来源命令和每个文件的状态。
- 外部 README 原文必须保存为 `.txt`，避免本仓库 Markdown 链接检查误判。
- 分析、判断、采用建议和沉淀路径写回上一级 `README.md`、`analysis.md` 或 `decisions.md`。
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# raw 事实层
本目录保存 `datawhalechina/vibe-vibe` 的本地原始材料快照。
这里不写分析结论，只保存可复查的一手资料：
- `sources.yml`：来源清单、拉取时间、命令和文件状态。
- `repository/`：Git 仓库工作树；本目录由 `.gitignore` 忽略，只作为本地研究材料。
- `github-repo.raw.json`：GitHub 仓库元数据。
- `github-readme.raw.md.txt`：GitHub README 原文快照。
- `github-license.raw.txt`：GitHub license 原文快照；仓库无 license 时可能不存在。
- `github-root-contents.raw.json`：默认分支根目录内容快照。
- `github-languages.raw.json`：GitHub language 统计快照。
- `github-latest-release.raw.json`：最新 release 快照；无 release 时可能不存在。
`repository/` 是外部源码快照，不参与本仓库 Markdown、链接、README/AGENTS 覆盖检查。原始 README 使用 `.txt` 后缀保存，避免其中的外部相对链接被本仓库 Markdown 链接检查误判。
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{
"Dockerfile": 444
}
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<p align="center">
<a href="./README.en.md">English</a> |
<a href="./README.md"><strong>简体中文</strong></a>
</p>
<p align="center">
<img src="./docs/public/logo.png" width="100" alt="Vibe Vibe"/>
</p>
<h1 align="center">Vibe Vibe </h1>
# Vibe Vibe —— 人人都能学会的 AI 编程（Vibe Coding）指南
> **面向零编程基础学习者的 AI 辅助编程系统化教程，从「我有一个想法」到「我做出了一个产品」，让人人都能成为 Builder。**
点击以访问教程主页：www.vibevibe.cn
### 核心理念
践行 OpenAI 联合创始人 **Andrej Karpathy** 提出的 Vibe Coding 理念——**从 Coder 到 Commander**：通过自然语言与 AI 对话，让编程从"写代码"转变为"对话式创作"。
> *"完全沉浸于编程的'氛围'中，忘记代码的存在。"*
### 快速开始
📖 **在线阅读**：[www.vibevibe.cn](https://www.vibevibe.cn)
| 你是谁 | 推荐起点 |
|-------|---------|
| 完全零基础 | 基础篇 → 第1章 觉醒 |
| 用过 ChatGPT 等大语言模型工具但没做过项目 | 基础篇 → 第2章 心法 |
| 有编程基础想学 Vibe Coding | 基础篇快速浏览 → 进阶篇 |
| 想直接动手做项目 | 基础篇 → 第4章 实战 |
| 想找项目练手 | 实践篇 |
### 私有化部署
如果你想在本地或内网环境部署本教程站点，仓库已经提供了可直接使用的 `Dockerfile` 和 `docker-compose.yml`：
```bash
docker compose up -d --build
```
默认访问地址为 `http://localhost:1024`。
更完整的部署方式、静态文件部署方案和离线环境注意事项，请查看[部署指南](./docs/deployment/index.md)。
### 教程定位
国内首个系统化的 Vibe Coding 开源教程，分为四大板块：
| 板块 | 定位 | 适合人群 |
|-----|------|---------|
| 📘 **基础篇** | AI 编程入门 + 心法 + 第一个项目 | 完全零基础、用过 ChatGPT 但没做过项目 |
| 📗 **进阶篇** | 16章"序言可阅读" · 从0到上线的避坑指南 | 想了解完整项目交付流程的开发者 |
| 📙 **实践篇** | 分人群项目实战 + 进阶技能训练 | 想通过动手练习巩固所学 |
| 📕 **优质文章篇** | 精选学习资源 + 行业前沿追踪 | 想持续学习、保持行业敏感度 |
- **为什么需要这份教程？** Vibe Coding 已成为全球趋势（越来越多的创业公司大部分代码由 AI 辅助生成），但国内学习资源碎片化严重，缺乏系统化、零基础友好、包含完整进阶路径的教程。
- **适合人群**：编程零基础者、大学生、创业者、传统程序员、职场人士，任何想用 AI 快速实现想法、提升工作效率或学习新范式的人。
### 进阶版预告：在线 IDE + Skills
我们即将推出**在线开发环境**，无需本地配置环境，打开浏览器即可开始学习：
- **云端 IDE** —— 内置完整的 Node.js 24、Python、Docker 等开发环境
- **50+ AI Skills** —— 预装丰富的 AI 辅助技能包，覆盖开发全流程
- **开箱即用** —— 无需安装任何软件，登录即可开始编程实践
让学习门槛降到最低，敬请期待！
### 学习产出
| 阶段 | 你将获得 |
|-----|---------|
| **基础篇** | 掌握 Vibe Coding 心法 · 用自然语言指挥 AI · 独立完成项目 · 部署上线能力 |
| **进阶篇** | 现代全栈技术栈 · 前后端架构 · 用户系统开发 · 生产级部署 · 工程化思维 |
## 贡献者名单
| 姓名 | 职责 | 简介 |
| :----| :---- | :---- |
| [符航康](https://www.hangkangfu.cn) | 项目负责人 & 核心贡献者 | 一位 AI 时代的原住民|
| [齐国皓](https://www.guohaoqi.cn) | 项目负责人 & 核心贡献者 | 现就读于新加坡国立大学计算机学院, 湖南大学金融科技协会创始人|
| 刘磊 | 「实践篇」贡献者、图像贡献者 | 中国科学院大学，一枚在职后端 Coder，热爱 Vibe，崇尚分享。 |
| 陈俊希 | 「优质文章篇」板块贡献者 | 湖南大学金融科技协会会长，湖南大学金融与统计学院24级本科生 |
| 金龙 |「实践篇」板块贡献者 | 北京大学学生创新学社AI俱乐部副部长，北京大学24级研究生|
| 舒璐璐 | 「实践篇」板块贡献者 | 湖南大学「麓山人文+」创始人，湖南大学岳麓书院23级本科生 |
## 目录
本教程分为**四大板块**，采用渐进式学习路径设计（点击展开详细目录）：
<details>
<summary><b>📘 基础篇：Vibe Coding 启示录（写给所有人的 AI 编程入门）</b></summary>
```
基础篇目录
│
├── 写在最前面
│ └── 找到你的位置
│
├── 第1章：觉醒 —— 为什么现在是编程最好的时代
│ ├── 1.1 编程已死，编程永生：从 Coder 到 Commander
│ ├── 1.2 核心概念：Vibe Coding 与 Spec Coding 详解
│ ├── 1.3 破除迷信：不懂英文、数学不好也能写代码吗？
│ ├── 1.4 工具初探：Cursor、Windsurf、Bolt.new 与 Replit 选型指南
│ └── 1.5 Hello World：你的第一个 3 分钟 AI 网页
│
├── 第2章：心法 —— 像产品经理一样思考
│ ├── 2.1 拒绝功能堆砌：为什么你的 AI 写不出复杂的 App？
│ ├── 2.2 MVP 思维：如何设计一个"能跑的最小版本"
│ ├── 2.3 灵魂三问：用户是谁？痛点在哪？为何用你？
│ └── 2.4 实战演练：拆解一个"背单词软件"的想法
│
├── 第3章：技法 —— 与 AI 对话的艺术
│ ├── 3.1 提示词工程基础：Context is King
│ ├── 3.2 用户旅程地图：把想法变成 AI 能懂的路径
│ ├── 3.3 编写第一份 PRD：让 AI 不再胡编乱造
│ └── 3.4 功能优先级 P0/P1/P2：学会对 AI 说"这个先不做"
│
├── 第4章：实战 —— 从 0 到 1 开发个人工具
│ ├── 4.1 环境准备：无需命令行的开发环境搭建
│ ├── 4.2 第一轮：生成静态页面 —— 先看"脸"
│ ├── 4.3 第二轮：注入逻辑与交互 —— 再长"脑"
│ ├── 4.4 第三轮：数据存储基础
│ └── 4.5 Debug 指南：当 AI 报错时，如何用 AI 修复 AI
│
├── 第5章：精进 —— 从"能用"到"好用"
│ ├── 5.1 后悔药：代码改崩了怎么办
│ ├── 5.2 见世面：把网页发到互联网上
│ ├── 5.3 护城河：AI 时代的安全意识
│ ├── 5.4 再进化：项目的持续迭代与优化
│ ├── 5.5 知边界：Vibe Coding 的能与不能
│ └── 5.6 启程前：本章总结与进阶预告
│
├── 结语：给未来的你
│
├── 下部预告：Vibe Coding 全栈实战教程
│
└── 附录
├── A. Prompt 速查清单
├── B. 常见错误与解决方案速查表
├── C. 术语表（中英对照）
├── D. 工具对比速查表
└── E. 项目 idea 清单
```
</details>
<details>
<summary><b>📗 进阶篇：从0到上线的避坑指南</b></summary>
本篇以**完整的产品交付流程**为主线，共16章，每章序言均可阅读：
```
进阶篇目录
│
├── 第1章：环境搭建、代码形态与包管理器
├── 第2章：开发工具与 AI 调教
├── 第3章：PRD 与文档驱动开发
├── 第4章：开发常识与技术栈
├── 第5章：代码运行状态与构建原理
├── 第6章：界面（UI）与交互（UX）
├── 第7章：环境变量与安全机制
├── 第8章：数据持久化与数据库
├── 第9章：功能测试流程与自动化脚本
├── 第10章：Localhost 与公网访问
├── 第11章：Git 版本控制与跨平台协作
├── 第12章：无服务器部署与 CI/CD 自动化
├── 第13章：域名解析原理与网络接入
├── 第14章：云服务器运维与项目部署
├── 第15章：SEO、分享与数据统计
└── 第16章：用户反馈与产品迭代
```
**技术栈**：Next.js 16 · React · TypeScript · Tailwind CSS · shadcn/ui · Drizzle ORM · PostgreSQL
</details>
<details>
<summary><b>📙 实践篇：分人群项目实战</b></summary>
```
实践篇目录
│
├── 基础板块（按人群分类）
│ ├── 文科生/商科生项目 —— 内容创作、数据展示类
│ ├── 理工科学生项目 —— 算法可视化、数据处理类
│ └── 职场人士项目 —— 工作流自动化、效率提升类
│
└── 进阶板块（基于 Sean's Stories 系列）
├── 核心技能 —— 上线应用、数据库、后端部署、用户认证
├── AI Agent 开发 —— RAG、向量数据库、MCP 集成
├── 全栈项目实战 —— SaaS、地图应用、移动应用
└── 工具与效率 —— n8n、GitHub 工作流、React/TS 进阶
```
</details>
<details>
<summary><b>📕 优质文章篇：精选学习资源</b></summary>
```
优质文章篇目录
│
├── 知名公司博客 —— OpenAI、Anthropic、Vercel 等技术博客
├── 优质播客 —— AI、开发者、创业者相关播客推荐
├── 研究报告 —— AI 发展报告、开发者调查、行业趋势
├── 优质 Newsletter —— 值得订阅的技术周刊
└── 开发者社区 —— Discord、Twitter、GitHub 优质资源
```
</details>
## 参与贡献
- 如果你发现了一些问题，可以提Issue进行反馈，如果提完没有人回复你可以联系[保姆团队](https://github.com/datawhalechina/DOPMC/blob/main/OP.md)的同学进行反馈跟进~
- 如果你想参与贡献本项目，可以提Pull request，如果提完没有人回复你可以联系[保姆团队](https://github.com/datawhalechina/DOPMC/blob/main/OP.md)的同学进行反馈跟进~
- 如果你对 Datawhale 很感兴趣并想要发起一个新的项目，请按照[Datawhale开源项目指南](https://github.com/datawhalechina/DOPMC/blob/main/GUIDE.md)进行操作即可~
## 关注我们
<div align=center>
<p>扫描下方二维码关注公众号：Datawhale</p>
<img src="https://raw.githubusercontent.com/datawhalechina/pumpkin-book/master/res/qrcode.jpeg" width = "180" height = "180">
</div>
## Star History
[![Star History Chart](https://api.star-history.com/svg?repos=datawhalechina/vibe-vibe&type=Date)](https://star-history.com/#datawhalechina/vibe-vibe&Date)
## LICENSE
<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="知识共享许可协议" style="border-width:0" src="https://img.shields.io/badge/license-CC%20BY--NC--SA%204.0-lightgrey" /></a><br />本作品采用<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/">知识共享署名-非商业性使用-相同方式共享 4.0 国际许可协议</a>进行许可。
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docs/research/datawhalechina-vibe-vibe/raw/sources.yml
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@@ -1,39 +0,0 @@
version: 1
domain_id: datawhalechina-vibe-vibe
object:
type: github_repository
name: datawhalechina/vibe-vibe
url: https://github.com/datawhalechina/vibe-vibe
pulled_at: '2026-07-02T22:47:14+00:00'
puller: scripts/fetch-research-raw.py
files:
- path: repository/
kind: git-working-tree
status: ok
source: 'git clone --depth=1 --single-branch --no-tags https://github.com/datawhalechina/vibe-vibe.git docs/research/datawhalechina-vibe-vibe/raw/repository'
- path: github-repo.raw.json
kind: repository-metadata
status: ok
source: 'gh repo view datawhalechina/vibe-vibe --json nameWithOwner,url,description,homepageUrl,isArchived,isFork,isMirror,defaultBranchRef,licenseInfo,primaryLanguage,repositoryTopics,stargazerCount,forkCount,watchers,createdAt,updatedAt,pushedAt,latestRelease --jq .'
- path: github-readme.raw.md.txt
kind: readme
status: ok
source: 'gh api repos/datawhalechina/vibe-vibe/readme -H Accept: application/vnd.github.raw'
- path: github-license.raw.txt
kind: license
status: missing_or_error
source: 'gh api repos/datawhalechina/vibe-vibe/license -H Accept: application/vnd.github.raw'
message: 'gh: Not Found (HTTP 404)'
- path: github-root-contents.raw.json
kind: root-contents
status: ok
source: 'gh api repos/datawhalechina/vibe-vibe/contents'
- path: github-languages.raw.json
kind: languages
status: ok
source: 'gh api repos/datawhalechina/vibe-vibe/languages'
- path: github-latest-release.raw.json
kind: latest-release
status: missing_or_error
source: 'gh api repos/datawhalechina/vibe-vibe/releases/latest'
message: 'gh: Not Found (HTTP 404)'
docs/research/earyantle-vibe-coding-skill/AGENTS.md
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@@ -1,24 +0,0 @@
# earyantLe/vibe-coding-skill 研究域 Agent 指南
本目录维护 `earyantLe/vibe-coding-skill` 的独立研究域。
## 目录职责
```text
earyantle-vibe-coding-skill/
├── README.md # 研究域入口和判断层
├── AGENTS.md # 本目录维护规则
├── domain.yml # 事实摘要层：仓库元数据、研究角色、来源证据
├── deep-dive.md # L2 结构深度研究、关键机制、迁移边界和验证任务
└── raw/ # 原始事实层：拉取到本地的一手材料快照
```
## 维护规则
- 本目录只研究 `earyantLe/vibe-coding-skill`，不要混入其他仓库的横向比较正文。
- 动态事实必须写入 `domain.yml.github_observed`，并更新 `observed_at`。
- `raw/` 保存原始事实层，必须通过 `python3 scripts/fetch-research-raw.py` 刷新。
- 不手工改写 `raw/*.raw.*` 文件；稳定事实摘要再同步到 `domain.yml`。
- README 只写判断、定位、使用方式和后续观察点，不堆外部 README 全文。
- 如果需要横向比较，在 `docs/research/README.md` 或新的对比文档中处理，不把本目录重新变成聚合域。
- 修改后运行 `make sync-doc-toc` 和 `make test`。
docs/research/earyantle-vibe-coding-skill/README.md
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@@ -1,59 +0,0 @@
# earyantLe/vibe-coding-skill 研究域
## 字多不看
- 本目录研究 `earyantLe/vibe-coding-skill` 这个外部仓库。
- 当前优先级：P3；研究角色：Vibe Coding Skill / SOP 化。
- GitHub 动态事实放在 `domain.yml`，观测日期为 2026-07-03。
## 快速导航
| 文档 | 定位 |
|:---|:---|
| [domain.yml](domain.yml) | 仓库事实快照、研究方向、优先级和来源证据。 |
| [analysis.md](analysis.md) | 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。 |
| [deep-dive.md](deep-dive.md) | L2 结构深度研究、关键机制、迁移边界和验证任务。 |
| [AGENTS.md](AGENTS.md) | 本研究域维护规则。 |
<details>
<summary><strong>完整细粒度目录（点击展开/收起）</strong></summary>
### 细粒度目录
- [domain.yml](domain.yml) - 仓库事实快照、研究方向、优先级和来源证据。
- [analysis.md](analysis.md) - 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。
- [deep-dive.md](deep-dive.md) - L2 结构深度研究、关键机制、迁移边界和验证任务。
- [AGENTS.md](AGENTS.md) - 本研究域维护规则。
</details>
## 使用方式
- 先读本 README 的判断，再读 `analysis.md` 的结构化研究结论，再读 `deep-dive.md` 的 L2 证据，
最后读 `domain.yml` 的事实字段。
- 需要引用 stars、forks、release、归档状态时，先重新核验 GitHub。
- 如果形成稳定方法论，再迁入 concepts、references、workflow 或 skills。
## 正文
### 研究定位
`earyantLe/vibe-coding-skill` 的当前研究定位是：Vibe Coding Skill / SOP 化。
### 当前判断
适合观察方法如何沉淀成 Skill 和 SOP。
### 观察字段
- GitHub URL：https://github.com/earyantLe/vibe-coding-skill
- 当前研究方向：`workflow-methodology`
- 当前优先级：P3
- 当前归档状态：`false`
- 主要语言：`None`
### 后续观察
- 是否有稳定文档结构、命令入口和可复用工作流。
- 是否能反哺本仓库的 concepts、references、workflow 或 skills。
- 是否存在许可证、归档状态、维护活跃度或生态迁移风险。
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# earyantLe/vibe-coding-skill 研究分析
## 本轮结论
`earyantLe/vibe-coding-skill` 的价值在“小型方法论如何封装成 Skill”。它不是大型教程，也不是复杂应用，
但它有 `SKILL.md`、`references/`、发布说明和提交流程，适合研究最小可发布 Skill 的骨架。
本仓最应该迁移的是 Skill 产品化边界：一个 Skill 不能只是长提示词，必须有触发条件、输入输出、
引用资料、约束、验证和发布检查。
## 本地证据
- 研究对象：`earyantLe/vibe-coding-skill`
- 当前研究角色：Vibe Coding Skill / SOP 化
- 原始仓库：`raw/repository/`
- 原始来源清单：`raw/sources.yml`
- 事实摘要：`domain.yml`
## 对标拆解
| 项 | 内容 |
|:---|:---|
| 参考对象 | `earyantLe/vibe-coding-skill` |
| 它解决的核心问题 | 把 Vibe Coding 方法封装成可调用 Skill |
| 核心机制 | `SKILL.md`、`references/`、`PUBLISH.md`、`SUBMISSION.md` |
| 真正带来结果的动作 | 让方法论从文档变成有入口、有资料、有发布流程的能力单元 |
| 可迁移做法 | Skill 最小结构、发布检查、引用资料组织 |
| 不可迁移条件 | 不把小型 Skill 当成完整方法论体系 |
| 下一步试用动作 | 为本仓 skills 建最小发布检查清单 |
## 改良迭代
| 改良目标 | 原模式 | 本仓版本 | 验证指标 |
|:---|:---|:---|:---|
| Skill 入口 | 单个 `SKILL.md` | 每个 skill 明确触发、边界、输入输出 | Agent 能判断何时调用 |
| 引用资料 | `references/` 支撑正文 | 引用资料按任务路由读取 | 不一次性加载无关资料 |
| 发布检查 | PUBLISH / SUBMISSION | 本仓 skill 校验和归档规则 | skill 可验证、可维护 |
## 可迁移清单
- 为 Skill 补触发条件、输入输出、边界和验证命令。
- 把长方法论拆成 `SKILL.md` 和 `references/`。
- 为发布和提交增加检查清单。
- 将 SOP 化经验转入 skills，而不是留在零散文档。
## 不可迁移清单
- 不把每个经验都做成 Skill。
- 不用 Skill 包装还没验证的方法。
- 不因为目录完整就认为能力可用。
## 验证动作
| 动作 | 成功信号 | 失败信号 |
|:---|:---|:---|
| 抽样一个本仓 skill 做发布检查 | 触发、输入、输出、验证都明确 | 只有提示词正文 |
| 把一条 SOP 转成 skill 候选 | 能说明为什么需要 skill | 文档已经足够却新增复杂度 |
| 校验 references 读取边界 | 只读任务相关资料 | skill 一启动就加载全部资料 |
## 沉淀判断
- 稳定结论进入 `skills/AGENTS.md`、`skills/README.md` 或 skill 创建规范。
- 本研究域保持 P3 Skill 骨架观察对象。
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# earyantLe/vibe-coding-skill 深度研究
## 研究级别
- 当前级别：L2 结构深度研究。
- 研究对象：`earyantLe/vibe-coding-skill`。
- 证据来源：本目录 `raw/` 下的 GitHub 元数据、README 快照、Skill 包和 references 工作树。
- 观察日期：2026-07-03。
## L2 结论
`earyantLe/vibe-coding-skill` 的核心价值是一个最小 Skill 产品化样本。它把 Vibe Coding 方法压成
`SKILL.md`、`references/`、`PUBLISH.md` 和 `SUBMISSION.md`，展示了“方法论如何变成可安装、
可触发、可交付的 Agent 能力包”。
对本仓最重要的启发是：Skill 不应该只是长 prompt。成熟 Skill 至少要包含触发条件、边界约束、
工作流、参考资料、质量检查和发布契约。
## 本地证据
- `raw/repository/SKILL.md`：Skill 主入口，包含触发条件、约束和工作流。
- `raw/repository/references/index.md`：参考资料索引，说明 Skill 可通过 references 分层读取。
- `raw/repository/references/workflow.md`：工作流资料。
- `raw/repository/references/quality-checklist.md`：质量检查资料。
- `raw/repository/references/glue-coding.md`：胶水式编码理念资料。
- `raw/repository/PUBLISH.md`：发布说明。
- `raw/repository/SUBMISSION.md`：提交说明。
- `domain.yml`：当前优先级为 P3，研究方向为 `workflow-methodology`。
## 关键机制
### Skill 是可分发能力包
该仓库不是只写一篇方法论文章，而是用 `SKILL.md` 承载入口，用 references 承载展开资料，用
发布/提交文档承载交付边界。这让经验从“读过”变成“可被 Agent 调用”。
### 主入口和参考资料分层
`SKILL.md` 负责触发和工作流，`references/` 负责细节。这个结构适合避免 Skill 主入口过长，
同时保留深度材料。
### 质量检查前置
`quality-checklist.md` 把质量要求显式化，说明 Skill 的交付不是生成文本结束，而是要形成检查项。
## 可迁移模式
- 为本仓 Skill 建立最小发布契约：触发条件、输入、输出、边界、验证和引用资料。
- 将长方法论拆成 `SKILL.md` 主入口和 `references/` 细节。
- 为 Skill 增加质量检查清单，防止只生成过程不验证结果。
- 将“是否应该成为 Skill”作为存在性门禁，避免把每条经验都拆成独立 Skill。
- 在 `skills/README.md` 或 Skill 契约中明确发布、归档和替代入口。
## 对本仓的影响
本仓已经有 `skills/`，但经验和 Skill 之间仍需要更硬的迁移规则。该对象提示我们：
- 经验短句不能直接等于 Skill，必须先证明可重复触发、可验证、可边界化。
- Skill 主入口要短，细节放 references，避免上下文污染。
- Skill 需要发布检查和归档策略，否则会变成 prompt 杂物间。
- `auto-skill` 和项目内技能库可以吸收这个结构，但不需要照搬其具体方法论表达。
## 风险和待验证项
- 仓库规模很小，stars、forks 和社区反馈不足，不能单独支撑通用标准。
- 缺少许可证信息，引用或复制内容前必须核验授权。
- Skill 是否有效需要实际任务集验证，不能只看结构。
- 本仓已有更复杂的 skill 体系，迁移时应只吸收发布契约和分层方式。
## 下一步 L3 验证任务
- 为本仓新增一份 Skill 发布检查清单，覆盖触发、输入、输出、边界、验证和归档。
- 抽样 3 个现有 Skill，检查主入口是否过长、references 是否足够分层。
- 为“经验 -> Skill”建立升级条件：高频、可重复、可验证、边界清晰。
- 给每个新增 Skill 增加失败信号：什么情况下不应调用该 Skill。
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version: 1
repo:
name: earyantLe/vibe-coding-skill
source_name: earyantLe/vibe-coding-skill
url: https://github.com/earyantLe/vibe-coding-skill
research:
domain_id: earyantle-vibe-coding-skill
domain_name: earyantLe/vibe-coding-skill 研究域
primary_direction: workflow-methodology
role: Vibe Coding Skill / SOP 化
priority: 3
why_study: 适合观察方法如何沉淀成 Skill 和 SOP。
github_observed:
observed_at: '2026-07-03'
source: gh repo view
stars: 0
forks: 0
archived: false
language: null
license: null
default_branch: main
pushed_at: '2026-03-23T12:51:33Z'
updated_at: '2026-03-23T12:51:41Z'
latest_release: null
homepage: ''
topics:
- ai-assistant
- canvas
- claude-skills
- glue-coding
- vibe-coding
source_evidence:
file: ChatGPT-中文Vibe Coding仓库 (2).md
line: 36
maintenance:
fact_policy: GitHub 动态字段只代表 observed_at 当日快照，更新结论前必须重新核验。
split_policy: 本目录已经是一等研究域；更深分析放入本目录新增文档。
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# raw/ Agent 指南
本目录是 `earyantLe/vibe-coding-skill` 的原始事实层。
## 维护规则
- 只保存从研究对象拉取的一手材料，不写分析判断。
- `repository/` 是本地 Git 工作树，刷新时由脚本 clone 或 fast-forward pull。
- 不手工改写 `*.raw.*` 文件内容；需要刷新时运行 `python3 scripts/fetch-research-raw.py`。
- `sources.yml` 必须记录拉取时间、来源命令和每个文件的状态。
- 外部 README 原文必须保存为 `.txt`，避免本仓库 Markdown 链接检查误判。
- 分析、判断、采用建议和沉淀路径写回上一级 `README.md`、`analysis.md` 或 `decisions.md`。
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# raw 事实层
本目录保存 `earyantLe/vibe-coding-skill` 的本地原始材料快照。
这里不写分析结论，只保存可复查的一手资料：
- `sources.yml`：来源清单、拉取时间、命令和文件状态。
- `repository/`：Git 仓库工作树；本目录由 `.gitignore` 忽略，只作为本地研究材料。
- `github-repo.raw.json`：GitHub 仓库元数据。
- `github-readme.raw.md.txt`：GitHub README 原文快照。
- `github-license.raw.txt`：GitHub license 原文快照；仓库无 license 时可能不存在。
- `github-root-contents.raw.json`：默认分支根目录内容快照。
- `github-languages.raw.json`：GitHub language 统计快照。
- `github-latest-release.raw.json`：最新 release 快照；无 release 时可能不存在。
`repository/` 是外部源码快照，不参与本仓库 Markdown、链接、README/AGENTS 覆盖检查。原始 README 使用 `.txt` 后缀保存，避免其中的外部相对链接被本仓库 Markdown 链接检查误判。
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{}
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# Vibe Coding CN Skill
> 基于 [tukuaiai/vibe-coding-cn](https://github.com/tukuaiai/vibe-coding-cn) 生成的 AI Skill
通过与 AI 结对编程，将想法变为现实的终极工作站。本 Skill 提供完整的 Vibe Coding 方法论、工作流程和实战指南。
---
## 📦 文件结构
```
.
├── README.md # 本文件 - 项目说明
├── SKILL.md # Skill 主文件（Claude Code 入口）
├── AGENTS.md # AI Agent 行为指南
└── references/
├── index.md # 参考资料索引
├── philosophy.md # Vibe Coding 哲学原理
├── glue-coding.md # 胶水编程方法论
├── canvas-dev.md # Canvas 白板驱动开发
├── language-layers.md # 12 层语言要素
├── workflow.md # 标准工作流
├── quality-checklist.md # 质量检查清单
└── agents-guidelines.md # AI Agent 行为准则（完整版）
```
---
## 🚀 快速开始
### 在 Claude Code 中使用
1. 将本仓库配置为 Claude Code 的 Skill
2. 或在对话中引用：`加载 vibe-coding-cn Skill`
### 使用方式
激活 Skill 后，你可以：
| 场景 | 示例指令 |
|:---|:---|
| 从零开发项目 | "用 Vibe Coding 方式帮我做一个 XXX" |
| 胶水编程 | "帮我找成熟的开源库来实现 XXX 功能" |
| 理解项目架构 | "用 Canvas 白板分析这个项目的架构" |
| 多 Agent 协作 | "用 tmux 蜂群模式并行处理这些任务" |
| 提升代码理解 | "用 12 层语言要素分析这段代码" |
---
## 📖 核心内容
### 方法论
| 主题 | 说明 | 入口 |
|:---|:---|:---|
| **Vibe Coding 哲学** | "一二三万物"核心理念 | [`SKILL.md`](./SKILL.md#核心哲学) |
| **胶水编程** | 能抄不写，能连不造 | [`references/glue-coding.md`](./references/glue-coding.md) |
| **Canvas 白板** | 图形驱动开发 | [`references/canvas-dev.md`](./references/canvas-dev.md) |
| **AI 蜂群协作** | tmux 多 Agent 系统 | [`SKILL.md`](./SKILL.md#ai-蜂群协作 tmux-多 agent-系统) |
### 工作流程
| 步骤 | 说明 | 入口 |
|:---|:---|:---|
| 1 | 游戏设计文档（GDD） | [`references/workflow.md`](./references/workflow.md) |
| 2 | 技术栈与 Agent 规则 | [`references/workflow.md`](./references/workflow.md) |
| 3 | 实施计划 | [`references/workflow.md`](./references/workflow.md) |
| 4 | 记忆库（Memory Bank） | [`references/workflow.md`](./references/workflow.md) |
| 5 | 增量式开发 | [`references/workflow.md`](./references/workflow.md) |
| 6 | 添加功能 | [`references/workflow.md`](./references/workflow.md) |
### 约束条件
| 类型 | 数量 | 入口 |
|:---|:---|:---|
| 通用开发约束 | 34 条 | [`SKILL.md`](./SKILL.md#通用开发约束 34 条核心) |
| 胶水开发约束 | 23 条 | [`SKILL.md`](./SKILL.md#胶水开发约束 23 条核心) |
| 系统提示词原则 | 15 条精要 | [`SKILL.md`](./SKILL.md#系统提示词构建原则精要版) |
### 能力提升
| 主题 | 说明 | 入口 |
|:---|:---|:---|
| **12 层语言要素** | 看懂 100% 代码的 12 个层级 | [`references/language-layers.md`](./references/language-layers.md) |
| **质量检查清单** | 各阶段检查项 | [`references/quality-checklist.md`](./references/quality-checklist.md) |
---
## 🎯 使用场景
| 场景 | 推荐文档 |
|:---|:---|
| 从零开始开发项目 | [`references/workflow.md`](./references/workflow.md) |
| 寻找开源库复用 | [`references/glue-coding.md`](./references/glue-coding.md) |
| 理解复杂项目架构 | [`references/canvas-dev.md`](./references/canvas-dev.md) |
| 看不懂代码 | [`references/language-layers.md`](./references/language-layers.md) |
| 确保代码质量 | [`references/quality-checklist.md`](./references/quality-checklist.md) |
| 配置 AI 行为 | [`AGENTS.md`](./AGENTS.md) |
---
## 📚 参考资料导航
完整参考资料索引 → [`references/index.md`](./references/index.md)
### 学习路径
**新手（从 0 到 1）：**
```
philosophy.md → workflow.md → glue-coding.md → language-layers.md
```
**进阶（提升效率）：**
```
glue-coding.md → canvas-dev.md → quality-checklist.md
```
**高级（架构与优化）：**
```
canvas-dev.md → language-layers.md → agents-guidelines.md
```
---
## 🙏 致谢
本 Skill 基于以下开源项目生成：
### 主要参考
| 项目 | 说明 |
|:---|:---|
| **[tukuaiai/vibe-coding-cn](https://github.com/tukuaiai/vibe-coding-cn)** | Vibe Coding 中文指南 - 本 Skill 的核心内容来源 |
### 感谢
感谢 [tukuaiai](https://github.com/tukuaiai) 及其贡献者们创建并维护这个优秀的开源项目，为 AI 辅助开发提供了系统化的方法论和实战指南。
---
## 📄 许可证
本项目继承自原仓库的 MIT 许可证。
---
## 🔗 相关资源
| 资源 | 链接 |
|:---|:---|
| Vibe Coding 中文指南（原仓库） | [GitHub](https://github.com/tukuaiai/vibe-coding-cn) |
| 提示词在线表格 | [Google Sheets](https://docs.google.com/spreadsheets/d/1Ifk_dLF25ULSxcfGem1hXzJsi7_RBUNAki8SBCuvkJA) |
| Claude Code 官方文档 | [Docs](https://docs.claude.com/) |
| Skills.sh | [Skills 大全](https://skills.sh/) |
---
## 📝 维护
- **最后更新**：2026-03-23
- **版本**：v2.0
- **贡献**：欢迎提交 Issue 和 PR
docs/research/earyantle-vibe-coding-skill/raw/github-repo.raw.json
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version: 1
domain_id: earyantle-vibe-coding-skill
object:
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name: earyantLe/vibe-coding-skill
url: https://github.com/earyantLe/vibe-coding-skill
pulled_at: '2026-07-02T22:47:14+00:00'
puller: scripts/fetch-research-raw.py
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kind: repository-metadata
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kind: readme
status: ok
source: 'gh api repos/earyantLe/vibe-coding-skill/readme -H Accept: application/vnd.github.raw'
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kind: license
status: missing_or_error
source: 'gh api repos/earyantLe/vibe-coding-skill/license -H Accept: application/vnd.github.raw'
message: 'gh: Not Found (HTTP 404)'
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kind: root-contents
status: ok
source: 'gh api repos/earyantLe/vibe-coding-skill/contents'
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message: 'gh: Not Found (HTTP 404)'
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# filipecalegario/awesome-vibe-coding 研究域 Agent 指南
本目录维护 `filipecalegario/awesome-vibe-coding` 的独立研究域。
## 目录职责
```text
filipecalegario-awesome-vibe-coding/
├── README.md # 研究域入口和判断层
├── AGENTS.md # 本目录维护规则
├── domain.yml # 事实摘要层：仓库元数据、研究角色、来源证据
├── analysis.md # L1 结构化研究结论、可借鉴点、风险和下一轮任务
├── deep-dive.md # L2 源码/结构深度研究、关键机制和可迁移模式
└── raw/ # 原始事实层：拉取到本地的一手材料快照
```
## 维护规则
- 本目录只研究 `filipecalegario/awesome-vibe-coding`，不要混入其他仓库的横向比较正文。
- 动态事实必须写入 `domain.yml.github_observed`，并更新 `observed_at`。
- `raw/` 保存原始事实层，必须通过 `python3 scripts/fetch-research-raw.py` 刷新。
- 不手工改写 `raw/*.raw.*` 文件；稳定事实摘要再同步到 `domain.yml`。
- README 只写判断、定位、使用方式和后续观察点，不堆外部 README 全文。
- `analysis.md` 写 L1 结构化理解；`deep-dive.md` 写 L2 源码证据、关键机制和可迁移模式。
- 如果需要横向比较，在 `docs/research/README.md` 或新的对比文档中处理，不把本目录重新变成聚合域。
- 修改后运行 `make sync-doc-toc` 和 `make test`。
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# filipecalegario/awesome-vibe-coding 研究域
## 字多不看
- 本目录研究 `filipecalegario/awesome-vibe-coding` 这个外部仓库。
- 当前优先级：P2；研究角色：国际 Vibe Coding 索引。
- GitHub 动态事实放在 `domain.yml`，观测日期为 2026-07-03。
## 快速导航
| 文档 | 定位 |
|:---|:---|
| [domain.yml](domain.yml) | 仓库事实快照、研究方向、优先级和来源证据。 |
| [analysis.md](analysis.md) | 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。 |
| [deep-dive.md](deep-dive.md) | L2 源码/结构深度研究、关键机制和可迁移模式。 |
| [AGENTS.md](AGENTS.md) | 本研究域维护规则。 |
<details>
<summary><strong>完整细粒度目录（点击展开/收起）</strong></summary>
### 细粒度目录
- [domain.yml](domain.yml) - 仓库事实快照、研究方向、优先级和来源证据。
- [analysis.md](analysis.md) - 本研究域的结构化研究结果、可借鉴点、风险和下一轮任务。
- [deep-dive.md](deep-dive.md) - L2 源码/结构深度研究、关键机制和可迁移模式。
- [AGENTS.md](AGENTS.md) - 本研究域维护规则。
</details>
## 使用方式
- 先读本 README 的判断，再读 `analysis.md` 和 `deep-dive.md` 的研究结论，最后读 `domain.yml`。
- 需要引用 stars、forks、release、归档状态时，先重新核验 GitHub。
- 如果形成稳定方法论，再迁入 concepts、references、workflow 或 skills。
## 正文
### 研究定位
`filipecalegario/awesome-vibe-coding` 的当前研究定位是：国际 Vibe Coding 索引。
### 当前判断
适合追踪概念、工具和资料生态，不适合作为单一学习主线。
### 观察字段
- GitHub URL：https://github.com/filipecalegario/awesome-vibe-coding
- 当前研究方向：`ecosystem-index`
- 当前优先级：P2
- 当前归档状态：`false`
- 主要语言：`None`
### 后续观察
- 是否有稳定文档结构、命令入口和可复用工作流。
- 是否能反哺本仓库的 concepts、references、workflow 或 skills。
- 是否存在许可证、归档状态、维护活跃度或生态迁移风险。
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# filipecalegario/awesome-vibe-coding 研究分析
## 本轮结论
`filipecalegario/awesome-vibe-coding` 的价值在国际语境和多语言 Vibe Coding 雷达。它提供概念定义、
跨语言表达和工具族分类，适合帮助本仓观察国际生态、术语翻译和资源候选。
它不是采用结论。awesome list 的问题是“广而浅”：能告诉你生态里有什么，但不能告诉你哪些真的适合
中文用户、哪些能进入工程工作流、哪些只是营销壳。
## 本地证据
- 研究对象：`filipecalegario/awesome-vibe-coding`
- 当前研究角色：国际 Vibe Coding 索引
- 原始仓库：`raw/repository/`
- 原始来源清单：`raw/sources.yml`
- 事实摘要：`domain.yml`
- 深度证据：`deep-dive.md`
## 对标拆解
| 项 | 内容 |
|:---|:---|
| 参考对象 | `filipecalegario/awesome-vibe-coding` |
| 它解决的核心问题 | 给国际 Vibe Coding 概念、工具和资料提供横向入口 |
| 核心机制 | 多语言 README、概念定义、工具族分类和贡献说明 |
| 真正带来结果的动作 | 用多语言和多类别降低生态发现成本 |
| 可迁移做法 | 国际术语对照、工具族分类、资源候选池、多语言表达观察 |
| 不可迁移条件 | 不直接采用国际工具推荐，不忽略中文网络、支付和学习环境 |
| 下一步试用动作 | 将工具族分类映射到本仓外部资源 schema 和关键词系统 |
## 改良迭代
| 改良目标 | 原模式 | 本仓版本 | 验证指标 |
|:---|:---|:---|:---|
| 国际雷达 | 多语言 awesome list | 本仓资源候选池和关键词候选 | 候选资源进入本地结构化字段 |
| 术语治理 | 多语言 README | 中文术语和英文术语成对记录 | 关键词系统能解释常见英文概念 |
| 工具筛选 | 按工具形态罗列 | 按用户场景、可访问性、维护状态筛选 | 资源推荐不再只看知名度 |
## 可迁移清单
- 提取 Vibe Coding 国际语境下的工具族和术语。
- 将重复出现的工具纳入资源候选，不直接纳入推荐。
- 观察多语言 README 如何处理术语翻译，反哺本仓关键词系统。
- 对高价值 CLI、IDE agent、local app 条目建立研究候选。
## 不可迁移清单
- 不把国际生态列表当作中文用户可用清单。
- 不把条目数量当作质量。
- 不把概念定义直接复制到本仓底层概念中。
## 验证动作
| 动作 | 成功信号 | 失败信号 |
|:---|:---|:---|
| 抽取 30 个条目做本地化筛选 | 能标出可用、待验证、不可用 | 只新增链接，无筛选结论 |
| 抽取术语对照 | 关键词系统新增中英对照候选 | 术语仍散落在资源标题里 |
| 将高频工具族映射到资源 schema | 分类覆盖更完整 | 分类仍无法容纳新工具 |
## 沉淀判断
- 稳定结果进入 `assets/external-resources/`、`docs/concepts/keyword-system.md` 和资源治理文档。
- 本研究域保持 P2 国际雷达，只有具体工具被验证后才升级为独立研究域。
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# filipecalegario/awesome-vibe-coding 深度研究
## 研究级别
- 当前级别：L2 源码/结构深度研究。
- 研究对象：`filipecalegario/awesome-vibe-coding`。
- 证据来源：本目录 `raw/` 下的 GitHub 元数据、README 快照和本地仓库工作树。
- 观察日期：2026-07-03。
## L2 结论
`filipecalegario/awesome-vibe-coding` 是国际 Vibe Coding 生态雷达。它的价值不在深度评测，
而在给出工具、平台、社区、任务管理和 AI coding 文档的横向分类视图。
对本仓最有价值的是分类体系和候选研究对象发现；它不应被当作推荐结论本身，因为 awesome list
缺少采用标准、风险等级、最后验证时间和本地事实层。
## 源码证据
- `raw/repository/README.md`：英文主清单，包含概念、工具、社区和文档分类。
- `raw/repository/README-CN.md`：中文入口。
- `raw/repository/README-JP.md`：日文入口。
- `raw/repository/README-KR.md`：韩文入口。
- `raw/repository/README-PT.md`：葡萄牙文入口。
- `raw/repository/contributing.md`：贡献规则。
- `raw/repository/code-of-conduct.md`：社区行为准则。
- README 分类包含 Browser-based Tools、IDEs and Code Editors、Mobile Apps、Plugins and Extensions、
Local Apps、Command Line Tools、Task Management for AI Coding、Documentation for AI Coding、
Communities & Job Boards、News and Social Media。
## 关键机制
### 分类是主要价值
awesome list 的第一价值是让读者知道生态里有哪些类型，而不是判断哪个最好。它适合作为资源雷达，
不适合作为采购或采用决策。
### 多语言 README 承担传播
多语言 README 说明 Vibe Coding 已经不是单一英文社区话题。它可以帮助本仓观察术语翻译、
跨语境表达和中文语境下哪些词需要本地化。
### AI coding 文档成为独立分类
清单中单独列出 Documentation for AI Coding，说明 `AGENTS.md`、`llms.txt`、rules、prompt
template、design docs 等已经从辅助材料变成生态基础设施。
### 任务管理进入 Agent 生态
Task Management for AI Coding 分类说明，当 agent 能写代码后，下一层需求会变成任务拆分、
并行执行、进度可视化、工作树隔离和验收管理。
## 可迁移模式
- 本仓外部资源表应吸收其工具族分类，但必须补足状态、来源、最后检查和风险字段。
- `docs/research/` 可以用该清单发现新的 P1/P2 候选研究对象。
- 关键词系统应吸收 browser tools、AI IDE、CLI agents、task management、AI coding docs 等分类。
- 对国际资源不直接翻译推荐，先做本地可用性、网络、支付、中文支持和维护状态验证。
## 对本仓的影响
本仓应把它定位为“资源发现层”，而不是“权威推荐层”：
- 发现新对象：进入 `assets/external-resources/` 或 `docs/research/`。
- 验证对象：拉 raw，建研究域，写 analysis/deep-dive。
- 稳定对象：下沉到 concepts、references、workflow 或 skills。
这个三段流比直接复制 awesome list 更适合长期维护。
## 风险和待验证项
- 清单缺少结构化元数据，无法直接判断活跃度、许可证、风险和适配中文用户的程度。
- 部分工具可能已经更名、停更或商业策略变化，需要重新核验。
- 本轮没有逐条验证清单链接和工具可用性。
## 下一步 L3 验证任务
- 从清单中抽取 coding agent、task management、AI coding docs 三类候选资源。
- 将候选资源进入 `assets/external-resources/`，补齐状态和检查时间。
- 对高价值工具建立单独研究域，而不是继续堆在资源清单。
- 将国际术语映射到本仓关键词系统。
docs/research/filipecalegario-awesome-vibe-coding/domain.yml
-41
View File
@@ -1,41 +0,0 @@
version: 1
repo:
name: filipecalegario/awesome-vibe-coding
source_name: filipecalegario/awesome-vibe-coding
url: https://github.com/filipecalegario/awesome-vibe-coding
research:
domain_id: filipecalegario-awesome-vibe-coding
domain_name: filipecalegario/awesome-vibe-coding 研究域
primary_direction: ecosystem-index
role: 国际 Vibe Coding 索引
priority: 2
why_study: 适合追踪概念、工具和资料生态，不适合作为单一学习主线。
github_observed:
observed_at: '2026-07-03'
source: gh repo view
stars: 4848
forks: 580
archived: false
language: null
license: cc0-1.0
default_branch: main
pushed_at: '2026-04-16T01:34:11Z'
updated_at: '2026-07-02T16:17:40Z'
latest_release: null
homepage: ''
topics:
- ai-agent
- ai-agents
- ai-coding-assistant
- ai-coding-tools
- cursor
- lovable
- vibe-coding
- awesome
- awesome-list
source_evidence:
file: ChatGPT-中文Vibe Coding仓库 (2).md
line: 49
maintenance:
fact_policy: GitHub 动态字段只代表 observed_at 当日快照，更新结论前必须重新核验。
split_policy: 本目录已经是一等研究域；更深分析放入本目录新增文档。

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