improve-codebase-architecture

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
category	development
risk	safe
source	community
source_repo	mattpocock/skills
source_type	community
date_added	2026-06-19
author	Matt Pocock
license	MIT
license_source	https://github.com/mattpocock/skills/blob/main/LICENSE
tags	["engineering","workflow","coding-agents"]
tools	["claude-code","codex-cli","cursor"]

Improve Codebase Architecture

When to Use

Use when this workflow matches the user request: Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

Source: mattpocock/skills (MIT).

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:

• Run the /codebase-design skill 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

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

Then use the Agent tool with subagent_type=Explore 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 so each run gets a fresh file. Open it for the user — on Linux, on macOS, on Windows — and tell them the absolute path.