From 663e331cf2f8024622ecc1f090e3e8799b80550f Mon Sep 17 00:00:00 2001 From: tradecatlabs <288998340+tradecatlabs@users.noreply.github.com> Date: Sat, 4 Jul 2026 07:13:59 +0800 Subject: [PATCH] docs: research - add trellis domain --- README.md | 3 +- assets/ai-citation/llms-full.txt | 3 + docs/README.md | 3 + docs/research/AGENTS.md | 9 +- docs/research/README.md | 4 + docs/research/harness/AGENTS.md | 2 +- docs/research/harness/README.md | 5 +- docs/research/mindfold-ai-trellis/AGENTS.md | 27 + docs/research/mindfold-ai-trellis/README.md | 73 +++ docs/research/mindfold-ai-trellis/analysis.md | 81 +++ .../research/mindfold-ai-trellis/deep-dive.md | 157 ++++++ docs/research/mindfold-ai-trellis/domain.yml | 37 ++ .../mindfold-ai-trellis/raw/AGENTS.md | 12 + .../mindfold-ai-trellis/raw/README.md | 16 + .../raw/github-languages.raw.json | 7 + .../raw/github-license.raw.txt | 235 +++++++++ .../raw/github-readme.raw.md.txt | 149 ++++++ .../raw/github-repo.raw.json | 46 ++ .../raw/github-root-contents.raw.json | 466 ++++++++++++++++++ .../mindfold-ai-trellis/raw/sources.yml | 39 ++ docs/research/research-transfer-synthesis.md | 10 +- .../research-value-application-map.md | 13 +- llms.txt | 1 + metadata/taxonomy.yml | 9 + 24 files changed, 1393 insertions(+), 14 deletions(-) create mode 100644 docs/research/mindfold-ai-trellis/AGENTS.md create mode 100644 docs/research/mindfold-ai-trellis/README.md create mode 100644 docs/research/mindfold-ai-trellis/analysis.md create mode 100644 docs/research/mindfold-ai-trellis/deep-dive.md create mode 100644 docs/research/mindfold-ai-trellis/domain.yml create mode 100644 docs/research/mindfold-ai-trellis/raw/AGENTS.md create mode 100644 docs/research/mindfold-ai-trellis/raw/README.md create mode 100644 docs/research/mindfold-ai-trellis/raw/github-languages.raw.json create mode 100644 docs/research/mindfold-ai-trellis/raw/github-license.raw.txt create mode 100644 docs/research/mindfold-ai-trellis/raw/github-readme.raw.md.txt create mode 100644 docs/research/mindfold-ai-trellis/raw/github-repo.raw.json create mode 100644 docs/research/mindfold-ai-trellis/raw/github-root-contents.raw.json create mode 100644 docs/research/mindfold-ai-trellis/raw/sources.yml diff --git a/README.md b/README.md index 09dff20..303ac65 100644 --- a/README.md +++ b/README.md @@ -532,10 +532,11 @@ * [**工程实践**](docs/references/quality-gates-and-pitfalls.md): 项目架构、代码组织、开发经验、AI 编程质量门禁与常见坑的统一入口。 * [**技术栈**](docs/references/technology-stack.md#reference-technology-stack-十四如何选择技术栈): 常见软件系统技术栈、选型维度、组合案例与初学者学习路径。 * [**研究域治理契约**](docs/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**](docs/research/research-value-application-map.md): 18 个研究域的用户价值、核心启示、应用位置和下沉路线。 +* [**研究价值与应用地图**](docs/research/research-value-application-map.md): 19 个研究域的用户价值、核心启示、应用位置和下沉路线。 * [**研究迁移综合**](docs/research/research-transfer-synthesis.md): 用对标拆解、改良迭代和杂交创新把研究转成可执行路线。 * [**Harness 工程解析**](docs/research/harness/harness-engineering.md): Harness Engineering 的工程控制、评估器与反馈闭环解析。 * [**Learn Harness Engineering 研究域**](docs/research/walkinglabs-learn-harness-engineering/README.md): Harness Engineering 课程、模板、Skill 与审计工具对标对象。 +* [**Trellis 研究域**](docs/research/mindfold-ai-trellis/README.md): 跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统研究对象。 * [**OpenAI Codex 研究域**](docs/research/openai-codex/README.md): 官方 coding agent 工具源码研究对象。 * [**Claude Code Best Practice 研究域**](docs/research/shanraisshan-claude-code-best-practice/README.md): Agentic Engineering 方法论对标研究对象。 * [**Cline 研究域**](docs/research/cline-cline/README.md): IDE/SDK/CLI 自主编码 Agent 研究对象。 diff --git a/assets/ai-citation/llms-full.txt b/assets/ai-citation/llms-full.txt index 6c4425a..6afc5f1 100644 --- a/assets/ai-citation/llms-full.txt +++ b/assets/ai-citation/llms-full.txt @@ -85,6 +85,9 @@ GEOFlow 的关键启发是：GEO 不是关键词堆砌，而是内容工程链 - docs/research/walkinglabs-learn-harness-engineering/README.md：Harness Engineering 课程、模板、Skill 与审计工具对标研究对象。 - docs/research/walkinglabs-learn-harness-engineering/analysis.md：walkinglabs/learn-harness-engineering 的结构化研究结论、可迁移做法、风险和验证动作。 - docs/research/walkinglabs-learn-harness-engineering/deep-dive.md：walkinglabs/learn-harness-engineering 的 L2 结构深度研究、关键机制和本仓应用建议。 +- docs/research/mindfold-ai-trellis/README.md：跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统研究对象。 +- docs/research/mindfold-ai-trellis/analysis.md：mindfold-ai/Trellis 的结构化研究结论、可迁移做法、风险和验证动作。 +- docs/research/mindfold-ai-trellis/deep-dive.md：mindfold-ai/Trellis 的 L2 结构深度研究、关键机制和本仓应用建议。 - docs/research/aider-ai-aider/README.md：终端 AI 结对编程工具研究对象。 - docs/research/aider-ai-aider/analysis.md：Aider-AI/aider 的结构化研究结论、可借鉴点、风险和下一轮任务。 - docs/research/aider-ai-aider/deep-dive.md：Aider-AI/aider 的 L2 源码/结构深度研究、关键机制和可迁移模式。 diff --git a/docs/README.md b/docs/README.md index a6885e0..1abb89a 100644 --- a/docs/README.md +++ b/docs/README.md @@ -84,6 +84,9 @@ - [walkinglabs/learn-harness-engineering 研究域](./research/walkinglabs-learn-harness-engineering/README.md) - Harness Engineering 课程、模板、Skill 与审计工具对标对象。 - [walkinglabs/learn-harness-engineering 研究分析](./research/walkinglabs-learn-harness-engineering/analysis.md) - 结构化研究结论、可迁移做法、风险和验证动作。 - [walkinglabs/learn-harness-engineering 深度研究](./research/walkinglabs-learn-harness-engineering/deep-dive.md) - L2 结构深度研究、关键机制和本仓应用建议。 +- [mindfold-ai/Trellis 研究域](./research/mindfold-ai-trellis/README.md) - 跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统。 +- [mindfold-ai/Trellis 研究分析](./research/mindfold-ai-trellis/analysis.md) - 结构化研究结论、可迁移做法、风险和验证动作。 +- [mindfold-ai/Trellis 深度研究](./research/mindfold-ai-trellis/deep-dive.md) - L2 结构深度研究、关键机制和本仓应用建议。 - [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。 diff --git a/docs/research/AGENTS.md b/docs/research/AGENTS.md index 11f986e..d69b741 100644 --- a/docs/research/AGENTS.md +++ b/docs/research/AGENTS.md @@ -31,6 +31,13 @@ research/ │ ├── deep-dive.md │ ├── raw/ │ └── AGENTS.md +├── mindfold-ai-trellis/ +│ ├── README.md +│ ├── domain.yml +│ ├── analysis.md +│ ├── deep-dive.md +│ ├── raw/ +│ └── AGENTS.md ├── ai-for-developers-awesome-vibe-coding/ │ ├── README.md │ ├── domain.yml @@ -107,7 +114,7 @@ research/ 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 18 个外部仓库研究域已经全部补齐，P3 只表示采用优先级低， +`deep-dive.md` 是 L2 产物；当前 19 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 diff --git a/docs/research/README.md b/docs/research/README.md index f2add4c..eaff717 100644 --- a/docs/research/README.md +++ b/docs/research/README.md @@ -17,6 +17,7 @@ | [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/) | 工程控制、评估器、反馈闭环与 AI 生成系统可靠性。 | | [walkinglabs/learn-harness-engineering 研究域](walkinglabs-learn-harness-engineering/) | Harness Engineering 课程、模板、Skill 与审计工具对标对象。 | +| [mindfold-ai/Trellis 研究域](mindfold-ai-trellis/) | 跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统。 | | [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/) | 终端 AI 结对编程工具。 | | [cline/cline 研究域](cline-cline/) | IDE/SDK/CLI 自主编码 Agent。 | @@ -49,6 +50,9 @@ - [walkinglabs/learn-harness-engineering 研究域](walkinglabs-learn-harness-engineering/README.md) - Harness Engineering 课程、模板、Skill 与审计工具对标对象。 - [walkinglabs/learn-harness-engineering 研究分析](walkinglabs-learn-harness-engineering/analysis.md) - 结构化研究结论、可迁移做法、风险和验证动作。 - [walkinglabs/learn-harness-engineering 深度研究](walkinglabs-learn-harness-engineering/deep-dive.md) - L2 结构深度研究、关键机制和本仓应用建议。 +- [mindfold-ai/Trellis 研究域](mindfold-ai-trellis/README.md) - 跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统。 +- [mindfold-ai/Trellis 研究分析](mindfold-ai-trellis/analysis.md) - 结构化研究结论、可迁移做法、风险和验证动作。 +- [mindfold-ai/Trellis 深度研究](mindfold-ai-trellis/deep-dive.md) - L2 结构深度研究、关键机制和本仓应用建议。 - [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。 diff --git a/docs/research/harness/AGENTS.md b/docs/research/harness/AGENTS.md index adc4433..a1f8b2b 100644 --- a/docs/research/harness/AGENTS.md +++ b/docs/research/harness/AGENTS.md @@ -28,7 +28,7 @@ harness/ - 不承载通用工程模板；稳定模板迁移到 `docs/references/`。 - 不承载可执行能力；可复用能力迁移到 `skills/`。 - 不把单个工具、单篇文章或单次实验直接包装成稳定结论。 -- 单个外部仓库的一手研究放到同级独立研究域，例如 `../walkinglabs-learn-harness-engineering/`。 +- 单个外部仓库的一手研究放到同级独立研究域，例如 `../walkinglabs-learn-harness-engineering/` 或 `../mindfold-ai-trellis/`。 ## 证据要求 diff --git a/docs/research/harness/README.md b/docs/research/harness/README.md index d19e3bf..29574c3 100644 --- a/docs/research/harness/README.md +++ b/docs/research/harness/README.md @@ -5,7 +5,7 @@ - 本目录把 Harness 作为独立研究对象维护。 - 稳定正文入口是 [Harness 工程解析](harness-engineering.md)。 - 研究重点是工程控制、评估器、反馈闭环、上下文注入、架构约束和长期治理。 -- 相关对标研究域是 [walkinglabs/learn-harness-engineering](../walkinglabs-learn-harness-engineering/README.md)。 +- 相关对标研究域是 [walkinglabs/learn-harness-engineering](../walkinglabs-learn-harness-engineering/README.md) 和 [mindfold-ai/Trellis](../mindfold-ai-trellis/README.md)。 - 成熟结论可晋升到 `docs/concepts/`、`docs/references/`、`docs/workflow/` 或 `skills/`。 ## 快速导航 @@ -14,6 +14,7 @@ |:---|:---| | [Harness 工程解析](harness-engineering.md) | 工程控制、评估器、反馈闭环与 AI 生成系统可靠性。 | | [walkinglabs/learn-harness-engineering 研究域](../walkinglabs-learn-harness-engineering/README.md) | Harness Engineering 课程、模板、Skill 与审计工具对标对象。 | +| [mindfold-ai/Trellis 研究域](../mindfold-ai-trellis/README.md) | 跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统。 | | [AGENTS](AGENTS.md) | Harness 研究对象目录操作规则。 |
@@ -23,6 +24,7 @@ - [Harness 工程解析](harness-engineering.md) - 工程控制、评估器、反馈闭环与 AI 生成系统可靠性。 - [walkinglabs/learn-harness-engineering 研究域](../walkinglabs-learn-harness-engineering/README.md) - Harness Engineering 课程、模板、Skill 与审计工具对标对象。 +- [mindfold-ai/Trellis 研究域](../mindfold-ai-trellis/README.md) - 跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统。 - [AGENTS](AGENTS.md) - Harness 研究对象目录操作规则。
@@ -31,6 +33,7 @@ - 需要理解 Harness Engineering 时，先读 Harness 工程解析。 - 需要看课程、模板、Skill 和审计工具的外部对标时，读 walkinglabs/learn-harness-engineering 研究域。 +- 需要看跨平台 Agent Harness、任务/规格/记忆控制面和多 Agent runtime 时，读 mindfold-ai/Trellis 研究域。 - 需要新增来源、评估框架、工具链样例或采用判断时，先检查 AGENTS 中的对象边界。 - 结论稳定后，再迁移到对应的概念、参考、流程或技能文档。 diff --git a/docs/research/mindfold-ai-trellis/AGENTS.md b/docs/research/mindfold-ai-trellis/AGENTS.md new file mode 100644 index 0000000..0434d53 --- /dev/null +++ b/docs/research/mindfold-ai-trellis/AGENTS.md @@ -0,0 +1,27 @@ +# mindfold-ai/Trellis 研究域 Agent 指南 + +本目录维护 `mindfold-ai/Trellis` 的独立研究域。 + +## 目录职责 + +```text +mindfold-ai-trellis/ +├── 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、可迁移做法、风险和验证动作 +├── deep-dive.md # L2 结构深度研究、关键机制和本仓应用建议 +└── 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 `mindfold-ai/Trellis`，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 结构证据、关键机制和可迁移模式。 +- Trellis 使用 AGPL-3.0 许可证；本仓只能研究机制和引用事实，不直接复制代码或模板实现。 +- 与通用 Harness 范式的横向比较放到 `docs/research/harness/` 或独立对比文档，不把本目录重新变成聚合域。 +- 修改后运行 `make sync-doc-toc` 和 `make test`。 diff --git a/docs/research/mindfold-ai-trellis/README.md b/docs/research/mindfold-ai-trellis/README.md new file mode 100644 index 0000000..700fdee --- /dev/null +++ b/docs/research/mindfold-ai-trellis/README.md @@ -0,0 +1,73 @@ +# mindfold-ai/Trellis 研究域 + +## 字多不看 + +- 本目录研究 `mindfold-ai/Trellis` 这个外部仓库。 +- 当前优先级：P1；研究角色：跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统。 +- GitHub 动态事实放在 `domain.yml`，观测日期为 2026-07-04。 +- 它最值得迁移的不是 AGPL 代码，而是把任务、规格、记忆、验证和多平台适配沉淀为仓库控制面的机制。 + +## 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、可迁移做法、风险和验证动作。 | +| [deep-dive.md](deep-dive.md) | L2 结构深度研究、关键机制和对本仓 Harness 体系的应用建议。 | +| [AGENTS.md](AGENTS.md) | 本研究域维护规则。 | + +
+完整细粒度目录（点击展开/收起） + +### 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、可迁移做法、风险和验证动作。 +- [deep-dive.md](deep-dive.md) - L2 结构深度研究、关键机制和对本仓 Harness 体系的应用建议。 +- [AGENTS.md](AGENTS.md) - 本研究域维护规则。 + +
+ +## 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、主页或主题标签时，先重新核验 GitHub。 +- 需要更新原始事实时，运行 `python3 scripts/fetch-research-raw.py mindfold-ai-trellis`。 +- 如果形成稳定方法论，再下沉到 `docs/research/harness/`、`docs/workflow/`、`scripts/` 或 `skills/`。 + +## 正文 + +### 研究定位 + +`mindfold-ai/Trellis` 的当前研究定位是：跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统。 + +### 当前判断 + +Trellis 是本仓 Harness 研究线的 P1 样本。它不是把 `AGENTS.md`、`CLAUDE.md` 或规则文件再包一层， +而是把 AI 编程过程做成仓库内可运行控制面： + +- 用 `.trellis/spec/` 保存团队约束，让 Agent 通过任务上下文加载规则，而不是靠模型记忆。 +- 用 `.trellis/tasks/` 保存 `prd.md`、`design.md`、`implement.md`、`implement.jsonl` 和 `check.jsonl`。 +- 用 `.trellis/workflow.md` 保存状态机和每轮注入的 breadcrumb，约束从计划、执行到收尾的相位。 +- 用 `.trellis/workspace/` 保存开发者会话记录，解决跨会话恢复和团队共享问题。 +- 用 CLI 同时生成 Claude Code、Codex、Cursor、OpenCode、Gemini、Kiro、Qoder、Copilot 等平台适配层。 +- 用 `channel`、`mem`、`task` 等核心原语把多 Agent 协作、会话检索和任务记录从文档推进到 runtime。 + +对本仓最有价值的点是：把“AI 协作经验”进一步升级为“可注入、可验证、可迁移、可升级的控制面”。 +经验句子容易被遗忘；任务、规格、上下文清单、状态机和验证命令能被下一轮 Agent 继续执行。 + +### 观察字段 + +- GitHub URL：https://github.com/mindfold-ai/Trellis +- 当前研究方向：`agent-harness-framework` +- 当前优先级：P1 +- 当前归档状态：`false` +- 主要语言：`TypeScript` + +### 后续观察 + +- `channel` runtime 是否继续成熟为通用多 Agent 协作层。 +- `mem` 是否从多平台会话检索扩展为更强的长期项目记忆。 +- Codex、Copilot、Gemini 等 pull-based 平台的上下文注入方式是否继续收敛。 +- `.trellis/spec/`、`.trellis/tasks/`、`.trellis/workflow.md` 的状态契约是否能稳定支撑团队协作。 +- AGPL-3.0 许可证边界下，哪些机制可借鉴、哪些代码和模板不能直接搬入本仓。 diff --git a/docs/research/mindfold-ai-trellis/analysis.md b/docs/research/mindfold-ai-trellis/analysis.md new file mode 100644 index 0000000..9d891a7 --- /dev/null +++ b/docs/research/mindfold-ai-trellis/analysis.md @@ -0,0 +1,81 @@ +# mindfold-ai/Trellis 研究分析 + +## 本轮结论 + +`mindfold-ai/Trellis` 的核心价值不是“又一个 AI 编程提示词集合”，而是把 AI 编程的关键过程做成 +仓库内控制面：规格注入、任务状态、上下文清单、会话记忆、验证 Agent、多平台适配和可升级模板。 + +本仓最应该迁移的是它的对象化治理方式：把上下文、约束和验证从聊天窗口中抽离出来，落到仓库文件、 +脚本和索引中，让不同 Agent 在不同会话中仍然执行同一套工作流。对本仓而言，最有价值的迁移方向是： + +- 把 `docs/research/` 的研究域继续强化为“对象目录 + raw 事实层 + 分析层 + 深度层 + 索引层”。 +- 把 `docs/research/harness/` 的概念研究补成任务、规格、记忆、验证四件套的控制面清单。 +- 把 `.trellis/tasks/` 的任务 artifact 思想迁移到重要文档任务：目的、约束、验收、验证命令和证据。 +- 把 `.trellis/spec/` 的规格注入思想迁移到本仓 AGENTS、README、llms 和 module context 的同步策略。 +- 把 `trellis-check`、`trellis-update-spec` 的收尾机制迁移为“验证后沉淀经验”的固定闭环。 + +## 本地证据 + +- 研究对象：`mindfold-ai/Trellis` +- 当前研究角色：跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统 +- 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 | `mindfold-ai/Trellis` | +| 它解决的核心问题 | AI 编程会话从零开始、规则分散、任务状态不稳定、验证闭环弱、多平台配置割裂、跨会话记忆无法复用 | +| 核心机制 | `.trellis/spec/`、`.trellis/tasks/`、`.trellis/workflow.md`、`.trellis/workspace/`、平台配置生成器、`channel` runtime、`mem` 检索、`task` schema | +| 真正带来结果的动作 | 把规则、任务、上下文、验证和会话历史变成仓库内可读、可执行、可升级的 artifact | +| 可迁移做法 | 规格注入、任务 artifact、jsonl 上下文清单、workflow breadcrumb、finish-work 收尾、spec update、跨平台适配矩阵 | +| 不可迁移条件 | 不复制 AGPL 代码或模板；不把本仓改造成 Trellis 运行时；不为了完整性引入过重的 CLI/runtime 所有权面 | +| 下一步试用动作 | 为本仓设计一份“任务 artifact 最小契约”：目标、约束、上下文清单、验证命令、沉淀路径和交接摘要 | + +## 改良迭代 + +| 改良目标 | 原模式 | 本仓版本 | 验证指标 | +|:---|:---|:---|:---| +| 上下文稳定 | Trellis 用 `.trellis/spec/` 和 jsonl 清单给 Agent 注入规则 | 本仓用 AGENTS、README、llms、研究域索引和 raw 事实层形成上下文路由 | 新会话能不用聊天记录也理解目录边界和验证路径 | +| 任务可恢复 | Trellis 每个任务有 PRD、设计、实现计划、上下文清单和状态 | 本仓重要研究/文档任务使用对象目录和分析层记录目的、证据、验收 | 中断后可从文件恢复下一步 | +| 验证闭环 | `trellis-check` 检查 diff，`trellis-update-spec` 沉淀新规则 | 本仓用 `make test`、链接检查、结构检查和研究域审计作为收尾门禁 | 交付前有可复跑命令和失败修复路径 | +| 多平台一致 | CLI 生成 Claude、Codex、Cursor、OpenCode 等平台配置 | 本仓维护根 `AGENTS.md`、`llms.txt`、`assets/ai-citation/llms-full.txt` 和工具配置入口 | 不同 AI 工具读取到同一套项目事实 | +| 会话记忆 | `mem` 检索 Claude、Codex、OpenCode、Pi 会话 | 本仓将稳定经验写入文档、研究域和技能，而不是依赖聊天历史 | 同类问题能被文档和索引复用 | + +## 可迁移清单 + +- 规格不靠记忆：项目规则必须写入仓库文件，并通过明确入口被 Agent 加载。 +- 任务不靠聊天：复杂任务必须有目标、上下文、验收、验证、状态和交接。 +- 上下文不全量塞入：用清单声明哪些文件为什么进入当前任务，减少噪声。 +- 状态不靠自觉：用 workflow phase 或检查清单强制计划、执行、验证、沉淀的顺序。 +- 验证不靠同一上下文自信：实现后必须有独立检查层，重要结论要能交叉审计。 +- 经验不只复盘：失败、约束和新模式要回写到规范层，让下一次自动加载。 +- 平台不各自为政：Claude、Codex、Cursor 等入口应共享同一项目事实，不维护冲突规则。 +- runtime 不默认引入：通道、worker 和会话检索机制值得研究，但本仓先采用轻量文档控制面。 + +## 不可迁移清单 + +- 不直接复制 Trellis 的 AGPL-3.0 代码、模板、hook 或脚本。 +- 不把 `.trellis/` 原样引入本仓作为新的真相源，除非先完成许可证、维护成本和门禁评估。 +- 不把多平台生成器当成所有项目的必选项；小型知识库先维护少量明确入口。 +- 不把 channel runtime 当成当前本仓必需能力；只有出现真实多 Agent 并发协作需求时再评估。 +- 不用复杂状态机替代清晰文档；只有任务会跨会话、跨 Agent 或需要审计时才提升治理等级。 + +## 验证动作 + +| 动作 | 成功信号 | 失败信号 | +|:---|:---|:---| +| 为本仓设计任务 artifact 最小契约 | 新会话能从文件读出目标、约束、上下文和验证 | 仍需要翻聊天记录才能继续 | +| 对现有研究域做一次 Trellis 式上下文清单审计 | 每个研究域都有事实层、分析层、索引层和沉淀路径 | 研究报告读完仍不知道可应用什么 | +| 抽取一条新增经验并回写到稳定入口 | 后续 Agent 能自动读取并执行 | 经验只留在本次回答里 | +| 评估多平台入口一致性 | `AGENTS.md`、`llms.txt`、`llms-full.txt` 指向一致 | 不同入口对项目结构说法冲突 | + +## 沉淀判断 + +- 稳定概念进入 `docs/research/harness/` 和 `docs/workflow/`。 +- 可执行任务 artifact 契约成熟后，可进入 `docs/references/` 或 `scripts/`。 +- 与 Skill、Agent、workflow 相关的可复用能力成熟后，再考虑进入 `skills/`。 +- 本研究域保持 P1，对齐 Agent Harness、任务控制面和多平台 AI 编程运行时。 diff --git a/docs/research/mindfold-ai-trellis/deep-dive.md b/docs/research/mindfold-ai-trellis/deep-dive.md new file mode 100644 index 0000000..60d1317 --- /dev/null +++ b/docs/research/mindfold-ai-trellis/deep-dive.md @@ -0,0 +1,157 @@ +# mindfold-ai/Trellis 深度研究 + +## 一句话判断 + +Trellis 的底层设计是：把 AI 编程从“聊天驱动”改造成“仓库控制面驱动”，让任务、规格、上下文、 +会话、验证和平台适配都成为可版本化对象。 + +## 结构拆解 + +| 层级 | 关键对象 | 作用 | +|:---|:---|:---| +| 仓库控制面 | `.trellis/` | 承载 workflow、spec、tasks、workspace、scripts、config，是 Agent 行为的本地真相源。 | +| 任务层 | `.trellis/tasks/{MM-DD-name}/` | 每个任务保存 `task.json`、`prd.md`、`design.md`、`implement.md`、`implement.jsonl`、`check.jsonl`。 | +| 规格层 | `.trellis/spec/` | 按 package/layer 管理编码规范、质量规则、架构约束和思考指南。 | +| 状态层 | `.trellis/workflow.md` | 定义 Plan、Execute、Finish 相位和 per-turn workflow-state breadcrumb。 | +| 记忆层 | `.trellis/workspace/` 与 `mem` | 保存会话日志，并从 Claude、Codex、OpenCode、Pi 等历史会话中检索上下文。 | +| 适配层 | `.claude/`、`.codex/`、`.cursor/`、`.opencode/` 等 | 把同一套 Trellis 工作流渲染到不同 AI coding 平台。 | +| runtime 层 | `channel`、worker、supervisor、event log | 支撑多 Agent 协作、消息路由、上下文挂载、worker 生命周期和中断。 | + +## 关键机制 + +### 1. 规格注入，而不是模型记忆 + +Trellis 的 `.trellis/spec/` 把团队规则拆成 package 和 layer，再通过任务的 `implement.jsonl`、`check.jsonl` +选择性注入给实现 Agent 与检查 Agent。这里的关键不是“多写文档”，而是让文档参与运行时： + +- spec 是长期规则； +- task artifact 是短期目标； +- jsonl manifest 是本次任务需要加载的上下文清单； +- implement/check Agent 只读与本次任务相关的部分，避免上下文膨胀。 + +对本仓的启示：`AGENTS.md`、`README.md`、`llms.txt`、`assets/ai-citation/llms-full.txt` 和研究域索引必须保持一致。 +它们不是说明书，而是 AI 进入仓库时的上下文入口。 + +### 2. 任务是执行单元，不是聊天片段 + +Trellis 的任务目录把“要做什么”拆成可恢复 artifact： + +- `task.json` 保存 24 字段的规范任务记录，包含 status、priority、assignee、branch、commit、PR、parent/children 等。 +- `prd.md` 保存需求、约束和验收。 +- `design.md` 保存边界、契约、数据流和取舍。 +- `implement.md` 保存执行顺序、验证命令、review gate 和回滚点。 +- `implement.jsonl`、`check.jsonl` 保存进入实现/检查阶段的上下文文件和原因。 + +对本仓的启示：复杂研究和文档治理任务不能只靠聊天推进。至少要能在文件里回答：目标是什么、上下文在哪里、 +验收是什么、验证命令是什么、未完成项是什么。 + +### 3. workflow breadcrumb 把状态注入每一轮 + +Trellis 在 `.trellis/workflow.md` 中维护 `[workflow-state:STATUS]` 块，并通过 hook 在每轮用户输入时注入当前状态。 +这解决的是 Agent 常见失败：忘记先计划、忘记进入检查、忘记提交前验证、忘记收尾沉淀。 + +关键设计点： + +- `no_task` 要求先判断是否创建任务。 +- `planning` 要求轻量任务至少有 PRD，复杂任务补齐 `design.md` 和 `implement.md`。 +- `in_progress` 明确实现、检查、更新 spec、commit、finish-work 的顺序。 +- Codex 可以走 inline 变体，适配平台子 Agent 隔离问题。 + +对本仓的启示：工作流规则不应该只写在长文档深处，而应出现在 Agent 每次开始任务时必读的位置。 + +### 4. 多平台适配不是复制多份规则 + +Trellis 的 `AI_TOOLS` registry 把 Claude Code、Cursor、OpenCode、Codex、Kilo、Kiro、Gemini、Antigravity、 +Devin、Qoder、CodeBuddy、Copilot、Droid、Pi、Reasonix、ZCode、Trae 等平台统一成配置对象。 +平台差异被压到 configurator、template 和 hook 能力矩阵中，核心工作流保持一致。 + +对本仓的启示：多 AI 工具支持应该有一个事实中心。根 `AGENTS.md`、`llms.txt`、`assets/ai-citation/llms-full.txt` +和工具目录不能各讲各的。 + +### 5. channel runtime 把多 Agent 协作变成事件系统 + +Trellis 的 `channel` API 暴露 channel、thread、message、context、worker、inbox、interrupt、watch、supervisor 等能力。 +CLI 侧提供 `create`、`send`、`wait`、`interrupt`、`spawn`、`run`、`list`、`messages`、`kill`、`post` 等命令。 + +这说明 Trellis 对 Agent 协作的理解不是“开几个窗口”，而是： + +- 共享事件日志； +- 明确 worker 身份； +- 消息有发送者、目标、线程和 delivery mode； +- 上下文可以挂到 channel 或 thread； +- supervisor 管理 worker 生命周期、空闲清理、超时和中断。 + +对本仓的启示：如果未来真的要做多 Agent 协同研究或 tmux worker 编排，应该优先采用“事件日志 + worker 状态 + 上下文挂载” +的模型，而不是只靠口头分工。 + +### 6. mem 把历史会话变成可检索材料 + +Trellis 的 `mem` 子系统从 Claude、Codex、OpenCode、Pi 等平台读取会话，提供 list、search、context、extract、projects。 +它的重点不是把所有聊天永久塞回提示词，而是让 Agent 能检索过去发生过的事实、决策和问题。 + +对本仓的启示：聊天记录可以辅助检索，但稳定知识必须进入仓库文档。真正的长期记忆不是“记住一切”， +而是把有价值的经验晋升到可维护结构。 + +## 可迁移模式 + +### 模式一：任务 artifact 最小契约 + +本仓可以设计轻量版任务契约，不需要引入完整 Trellis runtime： + +| 字段 | 最小含义 | +|:---|:---| +| 目的 | 本次任务要改变什么结果。 | +| 对象 | 涉及哪些文件、目录、研究域或流程。 | +| 约束 | 哪些地方不能动、哪些事实必须核验。 | +| 上下文 | 当前任务必须读取的文件和原因。 | +| 验收 | 什么状态算完成。 | +| 验证 | 可复跑的命令、检查或人工审计动作。 | +| 沉淀 | 哪些结论要进入 README、AGENTS、llms、research 或 skills。 | + +### 模式二：规格入口一致性 + +本仓已有多个 AI 入口。Trellis 的启示是：入口可以多，事实只能一个。 + +最低要求： + +- 根 `AGENTS.md` 说明仓库操作规则。 +- `llms.txt` 提供短上下文入口。 +- `assets/ai-citation/llms-full.txt` 提供完整 AI 引用入口。 +- `docs/research/README.md` 和 `docs/README.md` 提供研究域索引。 +- 新增研究域必须同步进入 metadata 和 llms。 + +### 模式三：验证后更新规格 + +Trellis 的 `trellis-update-spec` 思路可以转成本仓收尾规则： + +1. 完成修改。 +2. 运行质量门禁。 +3. 如果发现新的稳定规则、坑、流程或边界，回写到对应 AGENTS、README、docs 或 skills。 +4. 再提交。 + +这比“写完总结一下”更强，因为它要求下一次 Agent 能自动读到新规则。 + +## 不采用 Trellis 的边界 + +- AGPL-3.0 代码边界：本仓不能直接复制 Trellis 的实现、模板或 hook。 +- 项目形态边界：本仓是中文 Vibe Coding 知识库，不是 Trellis runtime 分发包。 +- 所有权边界：引入完整 CLI、多平台 configurator 和 channel runtime 会显著增加维护面。 +- 需求边界：当前本仓主要需要研究域、文档治理和质量门禁，不需要立即运行 worker supervisor。 + +## 对本仓的下一步建议 + +1. 在 `docs/research/harness/` 补一份“Agent Harness 控制面检查清单”。 +2. 为复杂文档任务定义轻量任务 artifact 契约。 +3. 建立“验证后沉淀规格”的收尾规则，把高频教训写回 AGENTS、README 或 skills。 +4. 对多 AI 入口做一致性检查，确保 `AGENTS.md`、`llms.txt`、`llms-full.txt` 和研究索引不漂移。 +5. 如果未来需要多 Agent 并发执行，再研究 channel runtime 或 `auto-tmux` 的事件化改造。 + +## 最小试用动作 + +下一轮可以选一个真实文档任务试用轻量 Trellis 模式： + +1. 写一个任务 artifact，明确目的、对象、约束、上下文、验收和验证。 +2. 执行修改。 +3. 用独立检查视角审计结果。 +4. 把新经验回写到稳定入口。 +5. 提交前确认索引和 AI 入口同步。 diff --git a/docs/research/mindfold-ai-trellis/domain.yml b/docs/research/mindfold-ai-trellis/domain.yml new file mode 100644 index 0000000..537f580 --- /dev/null +++ b/docs/research/mindfold-ai-trellis/domain.yml @@ -0,0 +1,37 @@ +version: 1 +repo: + name: mindfold-ai/Trellis + source_name: mindfold-ai/Trellis + url: https://github.com/mindfold-ai/Trellis +research: + domain_id: mindfold-ai-trellis + domain_name: mindfold-ai/Trellis 研究域 + primary_direction: agent-harness-framework + role: 跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统 + priority: 1 + why_study: 直接补强本仓 Harness 研究线，适合提炼任务控制面、规格注入、多平台 Agent 适配和会话记忆机制。 +github_observed: + observed_at: '2026-07-04' + source: gh repo view + stars: 11728 + forks: 661 + archived: false + language: TypeScript + license: AGPL-3.0 + default_branch: main + pushed_at: '2026-07-02T04:33:18Z' + updated_at: '2026-07-03T22:44:18Z' + latest_release: null + homepage: https://docs.trytrellis.app + topics: + - agentic-coding + - ai-workflow + - codex + - harness + - claudecode +source_evidence: + file: user-provided GitHub URL + line: null +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。 diff --git a/docs/research/mindfold-ai-trellis/raw/AGENTS.md b/docs/research/mindfold-ai-trellis/raw/AGENTS.md new file mode 100644 index 0000000..1af18c6 --- /dev/null +++ b/docs/research/mindfold-ai-trellis/raw/AGENTS.md @@ -0,0 +1,12 @@ +# raw/ Agent 指南 + +本目录是 `mindfold-ai/Trellis` 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`。 diff --git a/docs/research/mindfold-ai-trellis/raw/README.md b/docs/research/mindfold-ai-trellis/raw/README.md new file mode 100644 index 0000000..97349a7 --- /dev/null +++ b/docs/research/mindfold-ai-trellis/raw/README.md @@ -0,0 +1,16 @@ +# raw 事实层 + +本目录保存 `mindfold-ai/Trellis` 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。 diff --git a/docs/research/mindfold-ai-trellis/raw/github-languages.raw.json b/docs/research/mindfold-ai-trellis/raw/github-languages.raw.json new file mode 100644 index 0000000..9701680 --- /dev/null +++ b/docs/research/mindfold-ai-trellis/raw/github-languages.raw.json @@ -0,0 +1,7 @@ +{ + "TypeScript": 2044535, + "Python": 777390, + "JavaScript": 162160, + "HTML": 14591, + "Shell": 12336 +} diff --git a/docs/research/mindfold-ai-trellis/raw/github-license.raw.txt b/docs/research/mindfold-ai-trellis/raw/github-license.raw.txt new file mode 100644 index 0000000..0c97efd --- /dev/null +++ b/docs/research/mindfold-ai-trellis/raw/github-license.raw.txt @@ -0,0 +1,235 @@ +GNU AFFERO GENERAL PUBLIC LICENSE +Version 3, 19 November 2007 + +Copyright (C) 2007 Free Software Foundation, Inc. + +Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. + + Preamble + +The GNU Affero General Public License is a free, copyleft license for software and other kinds of works, specifically designed to ensure cooperation with the community in the case of network server software. + +The licenses for most software and other practical works are designed to take away your freedom to share and change the works. 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If not, see . + +Also add information on how to contact you by electronic and paper mail. + +If your software can interact with users remotely through a computer network, you should also make sure that it provides a way for users to get its source. For example, if your program is a web application, its interface could display a "Source" link that leads users to an archive of the code. There are many ways you could offer source, and different solutions will be better for different programs; see section 13 for the specific requirements. + +You should also get your employer (if you work as a programmer) or school, if any, to sign a "copyright disclaimer" for the program, if necessary. For more information on this, and how to apply and follow the GNU AGPL, see . diff --git a/docs/research/mindfold-ai-trellis/raw/github-readme.raw.md.txt b/docs/research/mindfold-ai-trellis/raw/github-readme.raw.md.txt new file mode 100644 index 0000000..9c84539 --- /dev/null +++ b/docs/research/mindfold-ai-trellis/raw/github-readme.raw.md.txt @@ -0,0 +1,149 @@ +

+ + + +Trellis Logo + +

+ +

+An out-of-the-box engineering framework for AI coding.
+AI writes code fast, but every session it starts from scratch — no memory of your project, your conventions, or your team's requirements. Trellis persists specs, tasks, and memory into your repo, so any coding agent works to your engineering standards. +

+ +

+简体中文 • +Docs • +Quick Start • +Supported Platforms • +Use Cases +

+ +

+npm version +npm downloads +license +stars +docs +Discord +open issues +open PRs +Ask DeepWiki +Ask ChatGPT +

+ +

+Trellis workflow demo +

+ +## Why Trellis? + +| Capability | What it changes | +| --- | --- | +| **Auto-injected specs** | Write conventions once in `.trellis/spec/`, then let Trellis inject the relevant context into each session instead of repeating yourself. | +| **Task-centered workflow** | Keep PRDs, implementation context, review context, and task status in `.trellis/tasks/` so AI work stays structured. | +| **Project memory** | Journals in `.trellis/workspace/` preserve what happened last time, so each new session starts with real context. | +| **Team-shared standards** | Specs live in the repo, so one person's hard-won workflow or rule can benefit the whole team. | +| **Multi-platform setup** | Bring the same Trellis structure to 16 AI coding platforms instead of rebuilding your workflow per tool. | + +## Prerequisites: + +- **Node.js** >= 18 +- **Python** >= 3.9 + +## Quick Start + +```bash +# 1. Install Trellis +npm install -g @mindfoldhq/trellis@latest + +# 2. Initialize in your repo +trellis init -u your-name + +# 3. Or initialize with the platforms you actually use +trellis init --cursor --opencode --codex -u your-name +``` + +See the [Quick Start](https://docs.trytrellis.app/start/install-and-first-task) and [Supported Platforms](https://docs.trytrellis.app/advanced/multi-platform) guides for setup details. + +## How to Use + +The workflow is simple: + +1. **Describe what you want** in natural language. +2. **Brainstorm** with the AI one question at a time until the PRD is clear, then implementation begins. +3. **Let it run** — the AI calls Trellis Implement and auto-checks the result against specs, lint, type-check, and tests. +4. **Type `/trellis:finish-work`** when the work is done or the session context fills up. Trellis archives the task and updates journals. + +## How It Works + +Trellis runs a 4-phase loop with auto-invoked skills and sub-agents: + +1. **Plan** — `trellis-brainstorm` walks through requirements one question at a time and writes `prd.md`. Research-heavy items go to a `trellis-research` sub-agent. The result is curated specs + research files referenced from `implement.jsonl` / `check.jsonl`. +2. **Implement** — a `trellis-implement` sub-agent writes code from the PRD with the curated context auto-injected, no git commit. +3. **Verify** — a `trellis-check` sub-agent reviews the diff against specs and runs lint, type-check, and tests, self-fixing where it can. +4. **Finish** — a final check runs, then `trellis-update-spec` promotes new learnings back into `.trellis/spec/` so the next session starts smarter. + +## Resources + +| Need | Link | +| ------------------------------- | ------------------------------------------------------------------------------ | +| Install Trellis in a repo | [Quick Start](https://docs.trytrellis.app/start/install-and-first-task) | +| Understand platform differences | [Supported Platforms](https://docs.trytrellis.app/advanced/multi-platform) | +| See the workflow in practice | [Real-World Scenarios](https://docs.trytrellis.app/start/real-world-scenarios) | +| Start from spec templates | [Spec Templates](https://docs.trytrellis.app/templates/specs-index) | +| Track releases | [Changelog](https://docs.trytrellis.app/changelog) | + +## FAQ + +
+How is Trellis different from CLAUDE.md, AGENTS.md, or .cursorrules? + +Those files are useful entry points, but they tend to become monolithic. Trellis adds scoped specs, task PRDs, workflow gates, workspace memory, and platform-aware generated files around them. + +
+ +
+Is Trellis only for Claude Code? + +No. Trellis is a project layer that works across multiple coding agents and IDEs. + +
+ +
+Is Trellis for solo developers or teams? + +Both. Solo developers use it for memory and repeatable workflow. Teams get the larger benefit: shared standards, task boundaries, reviewable context, and platform portability. + +
+ +
+Do I have to write every spec file manually? + +No. Many teams start by letting AI draft specs from existing code and then tighten the important parts by hand. Trellis works best when you keep the high-signal rules explicit and versioned. + +
+ +
+Can teams use this without constant conflicts? + +Yes. Personal workspace journals stay separate per developer, while shared specs and tasks stay in the repo where they can be reviewed and improved like any other project artifact. + +
+ +## Star History + +[![Star History Chart](https://api.star-history.com/svg?repos=mindfold-ai/Trellis&type=Date)](https://star-history.com/#mindfold-ai/Trellis&Date) + +## Community & Resources + +- [Official Docs](https://docs.trytrellis.app/) +- [GitHub Issues](https://github.com/mindfold-ai/Trellis/issues) +- [Discord](https://discord.com/invite/tWcCZ3aRHc) +- [Tech Blog](https://docs.trytrellis.app/blog) + +

+Official Repository • +AGPL-3.0 License • +Built by Mindfold +

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mindfold-ai-trellis +object: + type: github_repository + name: mindfold-ai/Trellis + url: https://github.com/mindfold-ai/Trellis +pulled_at: '2026-07-03T23:09:26+00:00' +puller: scripts/fetch-research-raw.py +files: + - path: repository/ + kind: git-working-tree + status: ok + source: 'git -C docs/research/mindfold-ai-trellis/raw/repository pull --ff-only' + message: 'Already up to date.' + - path: github-repo.raw.json + kind: repository-metadata + status: ok + source: 'gh repo view mindfold-ai/Trellis --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/mindfold-ai/Trellis/readme -H Accept: application/vnd.github.raw' + - path: github-license.raw.txt + kind: license + status: ok + source: 'gh api repos/mindfold-ai/Trellis/license -H Accept: application/vnd.github.raw' + - path: github-root-contents.raw.json + kind: root-contents + status: ok + source: 'gh api repos/mindfold-ai/Trellis/contents' + - path: github-languages.raw.json + kind: languages + status: ok + source: 'gh api repos/mindfold-ai/Trellis/languages' + - path: github-latest-release.raw.json + kind: latest-release + status: missing_or_error + source: 'gh api repos/mindfold-ai/Trellis/releases/latest' + message: 'gh: Not Found (HTTP 404)' diff --git a/docs/research/research-transfer-synthesis.md b/docs/research/research-transfer-synthesis.md index c7e0f89..ca31e0f 100644 --- a/docs/research/research-transfer-synthesis.md +++ b/docs/research/research-transfer-synthesis.md @@ -3,8 +3,8 @@ ## 字多不看 - 研究不是证明“我看过资料”，而是把成熟对象拆成可迁移机制、不可迁移边界和可验证动作。 -- 本轮把 P1 研究对象合成为一条主线：Codex 负责执行控制面，Aider 负责 Git 编辑闭环，Cline 负责多入口平台化，Claude Code Best Practice 负责方法论资产化。 -- 当前 18 个研究域均已补齐 `deep-dive.md`，全量进入 L2 证据层。 +- 本轮把 P1 研究对象合成为一条主线：Codex 负责执行控制面，Trellis 负责 Agent Harness 任务/规格/记忆控制面，Aider 负责 Git 编辑闭环，Cline 负责多入口平台化，Claude Code Best Practice 负责方法论资产化。 +- 当前 19 个研究域均已补齐 `deep-dive.md`，全量进入 L2 证据层。 - 本仓不应该复制任何一个外部项目，而应该杂交成“AI 原生知识库控制面”。 - 下一步最小试用动作是：补 `scripts` 风险登记、补 Harness 检查表、补资源治理 schema、补工作流验证闭环。 @@ -30,6 +30,7 @@ |:---|:---|:---|:---|:---|:---| | `openai/codex` | 执行控制面 | 把配置、沙箱、执行策略、工具、技能和项目上下文显式建模 | `scripts` 风险分级、Agent 执行边界、技能输入输出契约 | 不复制 Rust/Bazel/CLI runtime，本仓不是 coding agent 产品 | 建立 `scripts/manifest.yml`，记录 owner、风险、输入、输出、dry-run 和 CI 状态 | | `walkinglabs/learn-harness-engineering` | Harness 课程到工具化 | 把 Agent 可靠性拆成指令、状态、验证、范围、生命周期、模板、Skill 和审计脚本 | 五子系统审计、feature state、init 验证入口、评估表、会话交接 | 不复制 VitePress 站点、多语言工程和 Electron 课程项目 | 为本仓 Harness 研究域补最小检查表，并抽样改写成文档仓库版本 | +| `mindfold-ai/Trellis` | Agent Harness 任务/规格/记忆控制面 | 把 AI 编程会话转成 `.trellis/spec`、`.trellis/tasks`、workflow breadcrumb、workspace、channel runtime 和多平台配置 | 任务 artifact 最小契约、规格入口一致性、验证后沉淀、jsonl 上下文清单、多 AI 入口同步 | 不复制 AGPL 代码或模板，不把本仓改造成 Trellis runtime | 设计本仓轻量任务 artifact 契约，并用一个复杂文档任务试跑 | | `Aider-AI/aider` | Git 驱动编辑闭环 | 让每次 AI 修改都进入 diff、lint/test、commit、回滚和审查链路 | 研究域和文档修改必须保留 diff 证据、门禁命令和失败修复记录 | 不复制 Python 实现、repo map 算法和完整交互式终端产品 | 建立“AI 修改 -> diff 审查 -> make test -> commit”工作流模板 | | `cline/cline` | 多入口 agent 平台 | 同一套能力暴露为 IDE、CLI、SDK、rules、skills、examples 和测试平台 | 为人类入口、AI 入口、脚本入口、skill 入口、资源入口和 metadata 入口写清协议 | 不提前做 SDK、服务端 hub 或复杂 UI | 梳理本仓入口矩阵，记录每个入口的输入、输出、owner 和验证命令 | | `shanraisshan/claude-code-best-practice` | 方法论资产化 | 把经验拆成 best practice、implementation、workflow、reports、config | 把经验短句下沉为概念、模板、流程、skill 或检查项 | 不照搬 Claude Code 生态绑定配置，不把个人偏好当通用标准 | 建立“经验 -> 产物类型 -> 验证方式”的分流表 | @@ -42,6 +43,7 @@ |:---|:---|:---|:---|:---| | `openai-codex` | coding-agent-tooling | 执行控制面 | `scripts/`、`workflow/`、`references/` | 建脚本风险登记表 | | `walkinglabs-learn-harness-engineering` | harness-engineering | Harness 课程、模板、Skill 与审计工具 | `docs/research/harness/`、`workflow/`、`scripts/`、`skills/` | 建最小 Harness 检查表 | +| `mindfold-ai-trellis` | agent-harness-framework | 任务、规格、记忆、验证和多平台适配控制面 | `docs/research/harness/`、`workflow/`、`metadata/`、`llms.txt` | 建任务 artifact 最小契约 | | `aider-ai-aider` | coding-agent-tooling | Git 驱动编辑闭环 | `workflow/` | 建 AI 修改到提交的证据模板 | | `cline-cline` | coding-agent-tooling | 多入口 agent 平台 | `metadata/`、`llms.txt`、`skills/` | 建入口矩阵 | | `shanraisshan-claude-code-best-practice` | agentic-engineering-methodology | 方法论资产化 | `concepts/`、`workflow/`、`skills/` | 建经验分流表 | @@ -67,8 +69,8 @@ | 改动点 | 原模式 | 本仓改良 | 验证指标 | |:---|:---|:---|:---| -| 研究域分析 | 结构观察和可借鉴点 | 对标拆解、迁移边界、试用动作 | 18 个研究域 `analysis.md` 都有可执行动作 | -| 深度研究 | L2 证据和关键机制 | 保留证据链，另写迁移综合 | 18 个研究域均有 `deep-dive.md` | +| 研究域分析 | 结构观察和可借鉴点 | 对标拆解、迁移边界、试用动作 | 19 个研究域 `analysis.md` 都有可执行动作 | +| 深度研究 | L2 证据和关键机制 | 保留证据链，另写迁移综合 | 19 个研究域均有 `deep-dive.md` | | 价值地图 | 用户价值说明 | 增加组合方案和验收指标 | 能回答“看完有什么用” | ### 第二轮：让研究进入仓库控制面 diff --git a/docs/research/research-value-application-map.md b/docs/research/research-value-application-map.md index 4293d72..9834920 100644 --- a/docs/research/research-value-application-map.md +++ b/docs/research/research-value-application-map.md @@ -2,10 +2,10 @@ ## 字多不看 -- 当前研究体系已经覆盖 18 个独立研究域，18 个均已完成 L2 深度研究。 +- 当前研究体系已经覆盖 19 个独立研究域，19 个均已完成 L2 深度研究。 - 这些研究不是为了介绍外部项目，而是为了把外部项目拆成可验证事实、核心机制、迁移边界和本仓可执行改进项。 -- 18 个研究域的 `analysis.md` 已统一为对标拆解、改良迭代、可迁移清单、不可迁移清单和验证动作格式。 -- 18 个研究域的 `deep-dive.md` 已补齐 L2 证据层、关键机制、迁移边界和 L3 验证任务。 +- 19 个研究域的 `analysis.md` 已统一为对标拆解、改良迭代、可迁移清单、不可迁移清单和验证动作格式。 +- 19 个研究域的 `deep-dive.md` 已补齐 L2 证据层、关键机制、迁移边界和 L3 验证任务。 - 用户获得的直接价值是少走弯路、看见范式、拿到可落地路线。 - 本仓获得的直接价值是形成 `getting-started`、`references`、`workflow`、`skills`、`assets`、`scripts` 和 `research` 的改进输入。 @@ -16,8 +16,8 @@ | 层级 | 数量 | 状态 | 说明 | |:---|---:|:---|:---| -| 研究域 | 18 | 已建立 | 每个外部仓库一个独立研究域，均有 raw 原始事实层、`analysis.md` 和 `deep-dive.md` | -| L2 深度研究 | 18 | 已完成 | 覆盖工具、课程、资源索引、项目实践、中文主题雷达、Harness 课程和归档工具样本 | +| 研究域 | 19 | 已建立 | 每个外部仓库一个独立研究域，均有 raw 原始事实层、`analysis.md` 和 `deep-dive.md` | +| L2 深度研究 | 19 | 已完成 | 覆盖工具、课程、资源索引、项目实践、中文主题雷达、Harness 课程、Agent Harness 框架和归档工具样本 | | L1 观察研究 | 0 | 已清空 | P3 仍是低采用优先级，不再代表研究深度缺口 | ## 用户能获得什么 @@ -76,7 +76,7 @@ ### 一、AI Coding 的底座是控制面 -来自 `openai/codex`、`aider`、`cline` 的共同启示是：成熟 coding agent 依赖控制面，而不是只依赖 +来自 `openai/codex`、`aider`、`cline`、`Trellis` 的共同启示是：成熟 coding agent 依赖控制面，而不是只依赖 聊天能力。 可迁移结论： @@ -141,6 +141,7 @@ |:---|:---|:---|:---| | `openai/codex` | 理解 coding agent 控制面 | `scripts/`、`skills/`、`references/` | 脚本风险分级、沙箱/审批清单、Agent 控制面模板 | | `learn-harness-engineering` | 理解 Harness 如何从概念变成课程、模板、Skill 和审计工具 | `docs/research/harness/`、`workflow/`、`scripts/`、`skills/` | 最小 Harness 检查表、feature state 样例、Agent 产出评估表 | +| `Trellis` | 理解跨平台 Agent Harness 如何把任务、规格、记忆和验证做成仓库控制面 | `docs/research/harness/`、`workflow/`、`metadata/`、`llms.txt` | 任务 artifact 最小契约、规格入口一致性检查、验证后沉淀规则 | | `aider` | 理解 Git 驱动 AI 修改闭环 | `workflow/`、`references/` | AI 修改到提交的标准流程、文档 map / repo map 机制 | | `cline` | 理解多入口 agent 平台 | `metadata/`、`llms.txt`、`skills/` | 人类入口、AI 入口、脚本入口、skill 入口的入口契约 | | `awesome-claude-code` | 理解资源治理 | `assets/external-resources/` | 资源 schema、生命周期字段、资源校验脚本 | diff --git a/llms.txt b/llms.txt index 9a1ae07..17eb0bc 100644 --- a/llms.txt +++ b/llms.txt @@ -56,6 +56,7 @@ vibe-coding-cn 是一个中文 Vibe Coding / AI 结对编程系统教程，帮 - docs/research/research-transfer-synthesis.md - docs/research/harness/harness-engineering.md - docs/research/walkinglabs-learn-harness-engineering/README.md +- docs/research/mindfold-ai-trellis/README.md - docs/research/openai-codex/README.md - docs/research/shanraisshan-claude-code-best-practice/README.md - docs/research/cline-cline/README.md diff --git a/metadata/taxonomy.yml b/metadata/taxonomy.yml index ebff0fa..c6a5d9b 100644 --- a/metadata/taxonomy.yml +++ b/metadata/taxonomy.yml @@ -190,6 +190,15 @@ documents: - path: docs/research/walkinglabs-learn-harness-engineering/deep-dive.md title: walkinglabs/learn-harness-engineering 深度研究 role: L2 结构深度研究、关键机制和本仓应用建议 + - path: docs/research/mindfold-ai-trellis/README.md + title: mindfold-ai/Trellis 研究域 + role: 跨平台 Agent Harness 框架、CLI 与任务/规格/记忆系统 + - path: docs/research/mindfold-ai-trellis/analysis.md + title: mindfold-ai/Trellis 研究分析 + role: 结构化研究结论、可迁移做法、风险和验证动作 + - path: docs/research/mindfold-ai-trellis/deep-dive.md + title: mindfold-ai/Trellis 深度研究 + role: L2 结构深度研究、关键机制和本仓应用建议 - path: docs/research/aider-ai-aider/README.md title: Aider-AI/aider 研究域 role: 终端 AI 结对编程工具