Agent Skills › FradSer/dotclaude › improve-codebase-architecture

improve-codebase-architecture

GitHub

扫描代码库以识别架构摩擦,利用特定设计词汇分析模块深度与耦合度,生成可视化HTML报告并提出重构建议,旨在提升代码的可测试性与AI导航能力。

mattpocock/skills/engineering/improve-codebase-architecture/SKILL.md FradSer/dotclaude

Trigger Scenarios

用户希望改进代码库架构 寻找重构机会

Install

npx skills add FradSer/dotclaude --skill improve-codebase-architecture -g -y
More Options

Non-standard path

npx skills add https://github.com/FradSer/dotclaude/tree/main/mattpocock/skills/engineering/improve-codebase-architecture -g -y

Use without installing

npx skills use FradSer/dotclaude@improve-codebase-architecture

指定 Agent (Claude Code)

npx skills add FradSer/dotclaude --skill improve-codebase-architecture -a claude-code -g -y

安装 repo 全部 skill

npx skills add FradSer/dotclaude --all -g -y

预览 repo 内 skill

npx skills add FradSer/dotclaude --list

SKILL.md

Frontmatter
{
    "name": "improve-codebase-architecture",
    "description": "Scans a codebase for deepening opportunities, presents them as a visual HTML report, then grills through the chosen one. Use when the user wants to improve codebase architecture or find refactoring opportunities.",
    "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 "mattpocock: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 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, 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 CONTEXT.md vocabulary for the domain, and the /mattpocock: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 for the full HTML scaffold, diagram patterns, and styling guidance.

Do NOT propose interfaces yet. After the file is written, use the AskUserQuestion tool to ask which candidate to explore, the candidates as options with your recommended one marked "(Recommended)".

CRITICAL: Scope before you scan — and never propose interfaces

Decide where to look before looking: follow the user's direction, or walk the commit history for hot spots — YAGNI. The report surfaces candidates only: do NOT propose interfaces yet — present the report and use the AskUserQuestion tool to ask which candidate to explore before any design work.

3. Grilling loop

Once the user picks a candidate, call the Skill tool with "mattpocock: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 "mattpocock: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 "mattpocock:codebase-design" and use its design-it-twice parallel sub-agent pattern.

Version History

  • 9815c4f Current 2026-09-28 12:03

    同步上游版本至HEAD,标准化跨技能调用术语,更新领域建模触发条件,应用破折号移除规范,并新增相关技能支持。

  • 6f2a0b2 2026-08-20 10:59

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2026-08-20 10:59

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