Improve codebase architecture
Skill tt-a1i/matt-skills-with-to-goal/skills/improve-codebase-architecture
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.From its SKILL.md
npx -y skills add tt-a1i/matt-skills-with-to-goal --skill improve-codebase-architectureAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 29 days oldThe repository was created 29 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
- 18 stars18 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
5.9 KB, ~1.3k tokens by cl100k_base, as published. Nobody here has run it
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-designskill 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.mdgives names to good seams; ADRs indocs/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 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 toCONTEXT.md. Create the file lazily if it doesn't exist. - Sharpening a fuzzy term during the conversation? Update
CONTEXT.mdright 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-designskill and use its design-it-twice parallel sub-agent pattern.
What ships with it: 2 files
6.7 KB alongside SKILL.md
agents/
- openai.yaml166 B
- HTML-REPORT.md6.5 KB
Gives 5 of the 12 instructions most architecture codebase skills give in ~1.3k tokens
Counted across 811 of the 1,134 authors here whose files we hold, read 2026-08-07
- Ask the user which candidate to explorehere, and in 45 of 811, across 15 files
- Apply the deletion test to suspected shallow moduleshere, and in 43 of 811, across 15 files
- Read any relevant architecture decision records firsthere, and in 31 of 811, across 8 files
- Use exact glossary terms in every suggestionin 30 of 811, across 10 files
- Accept dependencies instead of creating themin 24 of 811, across 5 files
- Include before and after visualisations for each candidatehere, and in 24 of 811, across 5 files
- Read the domain glossary before exploringhere, and in 24 of 811, across 6 files
- Return results instead of producing side effectsin 23 of 811, across 4 files
- Explore the codebase for shallow modules and frictionin 23 of 811, across 3 files
- Introduce seams only where things varyin 22 of 811, across 3 files
- Reduce the number of methodsin 21 of 811, across 2 files
- Design deep modules with small interfacesin 21 of 811, across 3 files
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.