Improve Codebase Architecture

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:

• Use the coding-engineer-skills: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, and don't drift into "component," "service," "API," or "boundary."
• The domain language in the active context's CONTEXT.md, when present, gives names to good seams; that context's ADRs and root system-wide ADRs record decisions this command should not re-litigate. If a root CONTEXT-MAP.md exists, resolve the active context from it first and ask when the scope is ambiguous.

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 active context's domain glossary when present, its relevant ADRs, and any root system-wide 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 single HTML file to the OS temp directory so nothing lands in the repo. Create it with the OS's secure unique temporary-file primitive (mktemp on POSIX or an exclusive create in %TEMP% on Windows); do not construct a timestamp-only path. Capture the returned absolute path, quote it when passing it to xdg-open on Linux or open on macOS; on Windows use start "" "<path>" so the quoted path is not treated as a window title. Report that same path to the user.

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, so state that opening it requires network access. Follow HTML-REPORT.md when escaping repository-derived content and configuring Mermaid. 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 the active context's CONTEXT.md vocabulary for the domain, and the coding-engineer-skills:codebase-design vocabulary for the architecture. If that glossary 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, use the coding-engineer-skills:grilling skill 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; use the coding-engineer-skills:domain-modeling skill to keep the domain model current as you go:

• Naming a deepened module after a concept not in the active CONTEXT.md? Add the term to that context's CONTEXT.md. Create the file lazily if it doesn't exist.
• Sharpening a fuzzy term during the conversation? Update the active context's 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? Use the coding-engineer-skills:codebase-design skill and its design-it-twice parallel sub-agent pattern.