Matt Pocock 工程方法论 - improve-codebase-architecture

improve-codebase-architecture：mattpocock/skills 方法论: engineering/improve-codebas，适用于工程实践、代码质量与开发流程优化。

Skill Documentation

Matt Pocock 工程方法论 - improve-codebase-architecture

摘要

improve-codebase-architecture：mattpocock/skills 方法论: engineering/improve-codebas，适用于工程实践、代码质量与开发流程优化。

> 来源: mattpocock/skills (141k stars) — Total TypeScript 创始人 Matt Pocock

> 类目: 工程方法论

> 原文件: skills/engineering/improve-codebase-architecture/SKILL.md

> 模型推荐: gpt-4.1 (代码工程)

这个 skill 是干嘛的

Matt Pocock (Total TypeScript, 141k stars) 沉淀下来的"日常代码工程动作"skill 模板。

每一个对应一个具体动作(代码评审 / TDD / 重构 / 文档对齐 / 任务交接),不是工具,是"该怎么干这件事"的工作流模板。

michael 强调"skill 要有相应的指导功能,指导用户使用",所以这里加了下面两节让 Agent 和用户对接。

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🤖 Agent 使用说明

1. 接到任务后先按这个 skill 的检查清单走一遍

2. 清单里如果出现"先做 X 才能做 Y"的红线 → 必须先完成 X

3. 跑完清单后开始动手(改代码 / 写文档 / 评审)

4. 完工前用 `verification-before-completion`(superpowers) 或 `verification` 类 step 自检

5. 任务量大时考虑用 `dispatching-parallel-agents`(superpowers) 或 `wayfinder`(mattpocock) 拆解

👤 用户需要做什么?

1. 告诉 Agent 你要做什么(一句话即可)

2. Agent 跑 skill 清单时不要打断 — 它可能在收集上下文

3. 如果 Agent 主动问你"代码评审要不要安排一个 reviewer"等决策点 → 直接回答

4. 完工后让 Agent 跑一遍自检再交回

5. 整个过程 Agent 自动化,不需要手工介入

---

原 skill 内容(mattpocock/skills/engineering/improve-codebase-architecture/SKILL.md)

---

name: improve-codebase-architecture

description: Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

disable-model-invocation: true

---

Improve Codebase Architecture

Surface architectural friction and propose **deepening opportunities** — refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.

This command is _informed_ by the project's domain model and built on a shared design vocabulary:

• Call the Skill tool with "codebase-design" for the architecture vocabulary (**module**, **interface**, **depth**, **seam**, **adapter**, **leverage**, **locality**) and its principles (the deletion test, "the interface is the test surface", "one adapter = hypothetical seam, two = real"). Use these terms exactly in every suggestion — don't drift into "component," "service," "API," or "boundary."
• The domain language in `CONTEXT.md` gives names to good seams; ADRs in `docs/adr/` record decisions this command should not re-litigate.

Process

1. Explore

**Scope before you scan — YAGNI.** Deepening a module pays off by making future changes to it easier, so put extra weight on the parts of the codebase that have recently changed. Decide *where* to look before you look:

• If the user named a direction — a module, a subsystem, a pain point — take it, and skip the inference below.
• Otherwise, walk back a good stretch of the commit history (`git log --oneline`) to find the codebase's hot spots — the files and areas that keep coming up — and let those paths pull your attention first. If the changes are scattered with no clear hot spot, widen the net.

Read the project's domain glossary (`CONTEXT.md`) and any ADRs in the area you're touching first.

Then spawn a sub-agent to walk the codebase. Don't follow rigid heuristics — explore organically and note where you experience friction:

• Where does understanding one concept require bouncing between many small modules?
• Where are modules **shallow** — interface nearly as complex as the implementation?
• Where have pure functions been extracted just for testability, but the real bugs hide in how they're called (no **locality**)?
• Where do tightly-coupled modules leak across their seams?
• Which parts of the codebase are untested, or hard to test through their current interface?

Apply the **deletion test** to anything you suspect is shallow: would deleting it concentrate complexity, or just move it? A "yes, concentrates" is the signal you want.

2. Present candidates as an HTML report

Write a self-contained HTML file to the OS temp directory so nothing lands in the repo. Resolve the temp dir from `$TMPDIR`, falling back to `/tmp` (or `%TEMP%` on Windows), and write to `<tmpdir>/architecture-review-<timestamp>.html` so each run gets a fresh file. Open it for the user — `xdg-open <path>` on Linux, `open <path>` on macOS, `start <path>` on Windows — and tell them the absolute path.

The report uses **Tailwind via CDN** for layout and styling, and **Mermaid via CDN** for diagrams where a graph/flow/sequence reliably communicates the structure. Mix Mermaid with hand-crafted CSS/SVG visuals — use Mermaid when relationships are graph-shaped (call graphs, dependencies, sequences), and hand-built divs/SVG when you want something more editorial (mass diagrams, cross-sections, collapse animations). Each candidate gets a **before/after visualisation**. Be visual.

For each candidate, render a card with:

• **Files** — which files/modules are involved
• **Problem** — why the current architecture is causing friction
• **Solution** — plain English description of what would change
• **Benefits** — explained in terms of locality and leverage, and how tests would improve
• **Before / After diagram** — side-by-side, custom-drawn, illustrating the shallowness and the deepening
• **Recommendation strength** — one of `Strong`, `Worth exploring`, `Speculative`, rendered as a badge

End the report with a **Top recommendation** section: which candidate you'd tackle first and why.

**Use CONTEXT.md vocabulary for the domain, and the `/codebase-design` vocabulary for the architecture.** If `CONTEXT.md` defines "Order," talk about "the Order intake module" — not "the FooBarHandler," and not "the Order service."

**ADR conflicts**: if a candidate contradicts an existing ADR, only surface it when the friction is real enough to warrant revisiting the ADR. Mark it clearly in the card (e.g. a warning callout: _"contradicts ADR-0007 — but worth reopening because…"_). Don't list every theoretical refactor an ADR forbids.

See [HTML-REPORT.md](HTML-REPORT.md) for the full HTML scaffold, diagram patterns, and styling guidance.

Do NOT propose interfaces yet. After the file is written, ask the user: "Which of these would you like to explore?"

3. Grilling loop

Once the user picks a candidate, call the Skill tool with "grilling" to walk the decision tree with them — constraints, dependencies, the shape of the deepened module, what sits behind the seam, what tests survive.

Side effects happen inline as decisions crystallize — call the Skill tool with "domain-modeling" to keep the domain model current as you go:

• **Naming a deepened module after a concept not in `CONTEXT.md`?** Add the term to `CONTEXT.md`. Create the file lazily if it doesn't exist.
• **Sharpening a fuzzy term during the conversation?** Update `CONTEXT.md` right there.
• **User rejects the candidate with a load-bearing reason?** Offer an ADR, framed as: _"Want me to record this as an ADR so future architecture reviews don't re-suggest it?"_ Only offer when the reason would actually be needed by a future explorer to avoid re-suggesting the same thing — skip ephemeral reasons ("not worth it right now") and self-evident ones.
• **Want to explore alternative interfaces for the deepened module?** Call the Skill tool with "codebase-design" and use its design-it-twice parallel sub-agent pattern.

常见问题（FAQ）

使用「improve-codeba」这个 skill 能解决什么问题?

本 skill 专注于improve-codeba，mattpocock/skills 方法论: engineering/improve-codebase-architecture。它将相关流程标准化，帮助用户更快拿到可靠结果，减少重复手工操作。

什么情况下适合使用「improve-codeba」?

当你需要在improve-codebase-architecture相关工作中获得稳定、可复用的产出时最适合——无论是单次任务还是纳入日常工作流，都能直接调用。

使用「improve-codeba」前需要准备什么?

需要一个具体的项目或任务上下文，最好带有代码仓库或需求文档。