improve-codebase-architecture
mattpocock/skills · Agent Skill
掃描程式碼庫以找出改進的機會,並將其轉換為優先順序的視覺化報告。
前往安裝 ↓總覽
| 發布者 | |
|---|---|
| 儲存庫 | mattpocock/skills ↗ |
| 技能資料夾 | improve-codebase-architecture |
| 星 | 303,927 |
| 分支 | 25,575 |
| 附帶檔案 | 3 |
| 授權 | MIT |
| 最近更新 | 2026年10月22日 |
| 連結 | 技能原始碼 ↗ · 儲存庫 ↗ |
Mozgi 檢查
我們在技能檔案中發現的內容。詳細資訊需訂閱。
安裝
技能就是一個含 SKILL.md 的資料夾。選擇你的代理,在專案根目錄的終端機(macOS、Linux 或 Windows 的 Git Bash)執行指令。
把提示貼到 Claude、Codex 或其他助理:它會自行檢查並安裝技能。
Install the “improve-codebase-architecture” skill from mozgi.io (https://mozgi.io/skills/mattpocock-improve-codebase-architecture/) for me. 1. Download the archive: https://mozgi.io/skills/mattpocock-improve-codebase-architecture/download If it fails, take the skill folder from the source: https://github.com/mattpocock/skills/tree/main/skills/engineering/improve-codebase-architecture 2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me. 3. Put the “improve-codebase-architecture” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.). 4. Make sure <skills folder>/improve-codebase-architecture/SKILL.md exists. 5. Briefly tell me what this skill does and offer to try it on my task. If you cannot do a step yourself, tell me what to click or type.
git clone --depth 1 --branch main https://github.com/mattpocock/skills.git /tmp/skills mkdir -p .claude/skills cp -r /tmp/skills/skills/engineering/improve-codebase-architecture .claude/skills/improve-codebase-architecture
重新啟動 Claude Code — 技能就會出現在清單中,手動呼叫:/improve-codebase-architecture。要套用到所有專案,請放在 ~/.claude/skills。
git clone --depth 1 --branch main https://github.com/mattpocock/skills.git /tmp/skills mkdir -p .agents/skills cp -r /tmp/skills/skills/engineering/improve-codebase-architecture .agents/skills/improve-codebase-architecture
Codex 會從目前資料夾往上到儲存庫根目錄,在 .agents/skills 中尋找技能;用 /skills 或 $improve-codebase-architecture 呼叫。所有專案:~/.agents/skills。
git clone --depth 1 --branch main https://github.com/mattpocock/skills.git /tmp/skills mkdir -p .cursor/skills cp -r /tmp/skills/skills/engineering/improve-codebase-architecture .cursor/skills/improve-codebase-architecture
Cursor 啟動時會載入技能;在 Agent 聊天輸入「/」呼叫。Cursor 也會讀取 .claude/skills 與 .agents/skills。所有專案:~/.cursor/skills。
git clone --depth 1 --branch main https://github.com/mattpocock/skills.git /tmp/skills mkdir -p .gemini/skills cp -r /tmp/skills/skills/engineering/improve-codebase-architecture .gemini/skills/improve-codebase-architecture
任務符合時,Gemini CLI 會提議啟用技能,由你確認。所有專案:~/.gemini/skills。
安裝前請先檢視 SKILL.md 與相關檔案。點擊檔案即可預覽。
SKILL.md 內容
作者原文 · 唯讀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, and don't drift into "component," "service," "API," or "boundary."
- The domain language in
GLOSSARY.mdgives names to good seams; ADRs indocs/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 (GLOSSARY.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, with an 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 GLOSSARY.md vocabulary for the domain, and the /codebase-design vocabulary for the architecture. If GLOSSARY.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 ↗ 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
GLOSSARY.md? Add the term toGLOSSARY.md. Create the file lazily if it doesn't exist. - Sharpening a fuzzy term during the conversation? Update
GLOSSARY.mdright 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.
常見問題
improve-codebase-architecture 技能有什麼用途?
掃描程式碼庫以找出改進的機會,並將其轉換為優先順序的視覺化報告。
如何安裝 improve-codebase-architecture?
打開本頁的「安裝」區塊並選擇你的代理 — Claude Code、Codex、Cursor 或 Gemini CLI:那裡有把技能資料夾複製到正確位置的現成指令。也可以複製「透過助理」分頁中的提示,讓助理自行檢查並安裝技能。
improve-codebase-architecture 適用哪些 AI 模型?
技能是純 Markdown 指示(Agent Skills 格式),因此 improve-codebase-architecture 適用任何讀取 SKILL.md 的代理:Claude Code、Codex、Cursor、Gemini CLI、GitHub Copilot、OpenCode 等。只有在任務符合技能描述時,模型才會載入指示。
improve-codebase-architecture 是免費的嗎?
此技能由 mattpocock 公開發布,採用 MIT 授權。技能本身免費 — 你只需向 AI 供應商支付實際使用的 token 費用。
安裝技能安全嗎?
技能是代理會遵循的指示,安裝前請閱讀 SKILL.md 及相關檔案。技能資料夾中的腳本只有在代理執行時才會運行 — 留意它的動作,不要授予多餘權限。
技能和 MCP 伺服器或外掛有何不同?
MCP 伺服器或外掛為模型提供新工具 — 會執行並回傳結果的程式碼。技能提供的是知識與流程:如何處理任務、要遵循哪些步驟、好的成果長什麼樣子。它不需要伺服器或 API 金鑰。