improve-codebase-architecture
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
Skill by fderuiter
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/fderuiter-improve-codebase-architecture
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About
Use cases: documents, frontend
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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codeload.github.com· found in install command
Files it touches
~/.claude/skills/improve-codebase-architecture
What's inside
- Skill 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.
- License
- MIT
- Instructions
- 69 lines in SKILL.md · view on GitHub
Files (2)
- HTML-REPORT.md
- SKILL.md
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:
- 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 `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 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 interactive visual report
Generate the report as a structured Antigravity Artifact (in the session artifact directory) using `generative_ui` conventions, or as a self-contained HTML file in the OS temp directory so nothing unwanted lands in the repository.
In Antigravity, create an artifact containing structured cards with side-by-side Mermaid diagrams, carousel diff comparisons, and strength badges. If falling back to an OS temp file, resolve `$TMPDIR` (falling back to `/tmp` or `%TEMP%`), write to `<tmpdir>/architecture-review-<timestamp>.html`, and open it for the user (`start <path>` on Windows, `open <path>` on macOS, `xdg-open <path>` on Linux).
The report uses **Tailwind** for layout and styling, and **Mermaid** for diagrams where a graph/flow/sequence reliably communicates the structure. Mix Mermaid with custom 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, present the candidates to the user as selectable choices using `ask_question` (marking your top recommendation with `(Recommended)` and summarizing trade-offs, with chat fallback if absent): "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 using `ask_question`: 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 `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?** Call the Skill tool with "codebase-design" and use its design-it-twice parallel sub-agent pattern.From fderuiter/agy-skills, MIT.
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Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Aug 28, 2026 (2 months ago)
- Last release
- Aug 28, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/fderuiter/agy-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
improve-codebase-architecture skill. Agent Mart. https://agentmart.dev/skills/fderuiter-improve-codebase-architecture (last updated 2026-10-24)