improve-codebase-architecture

Files (3)

• HTML-REPORT.md
• SKILL.md
• openai.yaml · agents/

SKILL.md (first lines)

# 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:

- 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

**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 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 `<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 `/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](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, run the `/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 — run the `/domain-modeling` skill
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?** Run the
  `/codebase-design` skill and use its design-it-twice parallel sub-agent pattern.

From dotlas/skills, MIT.

More from dotlas/skills