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Improve Codebase Architecture

Matt PocockCommunityCreated by Matt Pocock

  • Skill
  • Research and analysis
  • Software development
  • MIT
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From the author

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
— the description by Matt Pocock

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to improving codebase architecture by identifying shallow modules and proposing refactors that increase depth, testability, and AI-navigability. It combines automated codebase scanning with a visual reporting phase and an interactive 'grilling' session to refine architectural decisions. The process is grounded in a specific design vocabulary and respects existing domain models and architectural decision records (ADRs).

What it does

  • Scans codebase hot spots to identify architectural friction and shallow modules.
  • Generates a visual HTML report using Tailwind and Mermaid to present refactoring candidates.
  • Provides before-and-after visualizations for proposed architectural changes.
  • Facilitates an interactive discussion to explore constraints and dependencies for chosen candidates.
  • Updates the project glossary and suggests new ADRs based on architectural decisions.
  • Uses a specific design vocabulary to ensure consistency in architectural discussions.

When to use it

  • When a codebase feels difficult to navigate or test due to shallow, tightly-coupled modules.
  • When you need to identify high-impact areas for refactoring based on recent commit history.
  • When you want to communicate architectural improvement proposals to a team using visual reports.
  • When you need to resolve architectural friction while maintaining alignment with existing domain models.

Advantages

  • Focuses on deepening modules to improve long-term maintainability and testability.
  • Uses visual reporting to make abstract architectural concepts easier to understand.
  • Integrates with existing project documentation like GLOSSARY.md and ADRs.
  • Prevents repetitive suggestions by allowing the recording of load-bearing architectural decisions.
  • Encourages a disciplined approach to design by using a shared, precise vocabulary.

Usage examples

“Scan the codebase for architectural improvements.”
The agent analyzes recent commit history, identifies shallow modules, and generates an HTML report with visual diagrams and recommendations.
“I want to focus on the Order intake module; can you find deepening opportunities there?”
The agent skips the general scan and performs a targeted analysis of the specified module, presenting specific refactoring candidates in an HTML report.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/mattpocock/improve-codebase-architecture/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip improve-codebase-architecture.zip -d .agents/skills

Documentation by Matt Pocock

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.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 (GLOSSARY.md) and any ADRs in the area you're touching first.

Then spawn a sub-agent with a fresh context window 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 to GLOSSARY.md. Create the file lazily if it doesn't exist.

  • Sharpening a fuzzy term during the conversation? Update GLOSSARY.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.

Files

HTML-REPORT.md

HTML Report Format

The architectural review is rendered as a single self-contained HTML file in the OS temp directory. Tailwind and Mermaid both come from CDNs. Mermaid handles graph-shaped diagrams reliably; hand-built divs and inline SVG handle the more editorial visuals (mass diagrams, cross-sections). Mix the two: don't lean on Mermaid for everything, it'll start to look generic.

Scaffold

<!doctype html>
<html lang="en">
  <head>
    <meta charset="utf-8" />
    <title>Architecture review for {{repo name}}</title>
    <script src="https://cdn.tailwindcss.com"></script>
    <script type="module">
      import mermaid from "https://cdn.jsdelivr.net/npm/mermaid@11/dist/mermaid.esm.min.mjs";
      mermaid.initialize({ startOnLoad: true, theme: "neutral", securityLevel: "loose" });
    </script>
    <style>
      /* small custom layer for things Tailwind doesn't cover cleanly:
         dashed seam lines, hand-drawn-feeling arrow heads, etc. */
      .seam { stroke-dasharray: 4 4; }
      .leak { stroke: #dc2626; }
      .deep { background: linear-gradient(135deg, #0f172a, #1e293b); }
    </style>
  </head>
  <body class="bg-stone-50 text-slate-900 font-sans">
    <main class="max-w-5xl mx-auto px-6 py-12 space-y-12">
      <header>...</header>
      <section id="candidates" class="space-y-10">...</section>
      <section id="top-recommendation">...</section>
    </main>
  </body>
</html>

Header

Repo name, date, and a compact legend: solid box = module, dashed line = seam, red arrow = leakage, thick dark box = deep module. No introduction paragraph. Straight into the candidates.

Candidate card

The diagrams carry the weight. Prose is sparse, plain, and uses the glossary terms (from the /codebase-design skill) without ceremony.

Each candidate is one <article>:

  • Title: short, names the deepening (e.g. "Collapse the Order intake pipeline").

  • Badge row: recommendation strength (Strong = emerald, Worth exploring = amber, Speculative = slate), plus a tag for the dependency category (in-process, local-substitutable, ports & adapters, mock).

  • Files: monospaced list, font-mono text-sm.

  • Before / After diagram: the centrepiece. Two columns, side by side. See patterns below.

  • Problem: one sentence. What hurts.

  • Solution: one sentence. What changes.

  • Wins: bullets, ≤6 words each. e.g. "Tests hit one interface", "Pricing logic stops leaking", "Delete 4 shallow wrappers".

  • ADR callout (if applicable): one line in an amber-tinted box.

No paragraphs of explanation. If the diagram needs a paragraph to be understood, redraw the diagram.

Diagram patterns

Pick the pattern that fits the candidate. Mix them. Don't make every diagram look the same. Variety is part of the point.

Mermaid graph (the workhorse for dependencies / call flow)

Use a Mermaid flowchart or graph when the point is "X calls Y calls Z, and look at the mess." Wrap it in a Tailwind-styled card so it doesn't feel parachuted in. Style with classDef to colour leakage edges red and the deep module dark. Sequence diagrams work well for "before: 6 round-trips; after: 1."

<div class="rounded-lg border border-slate-200 bg-white p-4">
  <pre class="mermaid">
    flowchart LR
      A[OrderHandler] --> B[OrderValidator]
      B --> C[OrderRepo]
      C -.leak.-> D[PricingClient]
      classDef leak stroke:#dc2626,stroke-width:2px;
      class C,D leak
  </pre>
</div>
Hand-built boxes-and-arrows (when Mermaid's layout fights you)

Modules as <div>s with borders and labels. Arrows as inline SVG <line> or <path> elements positioned absolutely over a relative container. Reach for this when you want the "after" diagram to feel like one thick-bordered deep module with greyed-out internals, since Mermaid won't render that with the right weight.

Cross-section (good for layered shallowness)

Stack horizontal bands (h-12 border-l-4) to show layers a call passes through. Before: 6 thin layers each doing nothing. After: 1 thick band labelled with the consolidated responsibility.

Mass diagram (good for "interface as wide as implementation")

Two rectangles per module: one for interface surface area, one for implementation. Before: interface rectangle is nearly as tall as the implementation rectangle (shallow). After: interface rectangle is short, implementation rectangle is tall (deep).

Call-graph collapse

Before: a tree of function calls rendered as nested boxes. After: the same tree collapsed into one box, with the now-internal calls shown faded inside it.

Style guidance

  • Lean editorial, not corporate-dashboard. Generous whitespace. Serif optional for headings (font-serif works well with stone/slate).

  • Colour sparingly: one accent (emerald or indigo) plus red for leakage and amber for warnings.

  • Keep diagrams ~320px tall so before/after sits comfortably side by side without scrolling.

  • Use text-xs uppercase tracking-wider for module labels inside diagrams, so they read as schematic, not as UI.

  • The only scripts are the Tailwind CDN and the Mermaid ESM import. The report is otherwise static: no app code, no interactivity beyond Mermaid's own rendering.

Top recommendation section

One larger card. Candidate name, one sentence on why, anchor link to its card. That's it.

Tone

Plain English, concise, but the architectural nouns and verbs come straight from the /codebase-design skill. Concision is not an excuse to drift.

Use exactly: module, interface, implementation, depth, deep, shallow, seam, adapter, leverage, locality.

Never substitute: component, service, unit (for module) · API, signature (for interface) · boundary (for seam) · layer, wrapper (for module, when you mean module).

Phrasings that fit the style:

  • "Order intake module is shallow: interface nearly matches the implementation."

  • "Pricing leaks across the seam."

  • "Deepen: one interface, one place to test."

  • "Two adapters justify the seam: HTTP in prod, in-memory in tests."

Wins bullets name the gain in glossary terms: "locality: bugs concentrate in one module", "leverage: one interface, N call sites", "interface shrinks; implementation absorbs the wrappers". Don't write "easier to maintain" or "cleaner code", because those terms aren't in the glossary and don't earn their place.

No hedging, no throat-clearing, no "it's worth noting that…". If a sentence could be a bullet, make it a bullet. If a bullet could be cut, cut it. If a term isn't in the /codebase-design glossary, reach for one that is before inventing a new one.

Requirements and compatibility

Written for: Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter

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Attribution and licence

Created by
Matt Pocock
Publisher
Matt Pocock (Community)
Source
mattpocock/skills · skills/engineering/improve-codebase-architecture · commit 4ae2317
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

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