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/improve-codebase-architecture

@4ae2317 official
by Matt Pocockmattpocock/skills312k stars
26,198
Run it yourself

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

Use this Skill: https://skilld.dev/gh/mattpocock/skills/improve-codebase-architecture

Nothing lands on disk. Nothing to clean up.

Fork this Skill

Edit a local copy. It keeps the author and licence.

SKILL.md

≈39 tokens for metadata: the name and description. ≈1.5k when used: this file. ≈1.7k more on demand in 2 files.

How this Skill uses context

Before choosing a Skill, your Agent reads its name and description. All available Skills share that space.

This Skill turns off automatic use in Claude Code. Its description stays out of the automatic Skill list by default.

Example settings and source

The example uses a 200k-token context and default Claude Code settings. The count includes the name, description, separators, and when_to_use when present. Codex also counts local file paths.

Skit's source and limits: Codex 0.160.1, Claude Code 2.1.292.

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 GLOSSARY.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 (GLOSSARY.md) and any ADRs in the area you're touching first.

Then spawn a sub-agent with a fresh context window 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 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 GLOSSARY.md vocabulary for the domain, and the /codebase-design vocabulary for the architecture. If GLOSSARY.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, call the Skill tool with "grilling" 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; 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 GLOSSARY.md? Add the term to GLOSSARY.md. Create the file lazily if it doesn't exist.
  • Sharpening a fuzzy term during the conversation? Update GLOSSARY.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.

Source: SKILL.md on GitHub

No rule matched.

skilld matched fixed text patterns in SKILL.md and file names. Patterns miss obfuscated code.

skilld run checks every file with the same patterns. It asks for approval before it loads a Skill with a behavior marked Needs approval.

1 warning10d5 checks · Risk SAFE
  • Gen Agent Trust Hub10d

    The skill is generally safe for development use but possesses a vulnerability surface for indirect prompt injection because it processes untrusted codebase data without explicit sanitization. It also generates HTML reports using a 'loose' security configuration for diagrams.

  • Socket10d

    No alerts

  • Snyk10d

    Risk: MEDIUM · 1 issue

  • Runlayer8mo

    2 files scanned · No issues

  • ZeroLeaks6mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at 4ae2317. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub last week.

Activeupdated last week
disable-model-invocation
true
  • Refactoring
  • architecture
  • codebase
  • modularity
  • testability
  • domain-driven-design
  • adr
  • seams
  • depth

README badge

README badge for mattpocock/skills/improve-codebase-architecture

Finds architectural friction in a codebase by identifying shallow modules and tightly-coupled seams, then proposes deepening refactors that increase leverage and locality. Uses domain language from CONTEXT.md and existing ADRs to ground suggestions, then walks through a grilling conversation to design the deepened module's interface.

Generated from the current SKILL.md.

Does this skill help me refactor an existing codebase, or does it design new architecture from scratch?
It surfaces architectural friction and proposes deepening opportunities in existing codebases — turning shallow modules into deep ones. It does not design greenfield architecture.
Does this skill read from CONTEXT.md and ADRs?
Yes. It uses domain language from CONTEXT.md and respects decisions recorded in docs/adr/ to avoid re-litigating settled choices and to ground suggestions in the project's own vocabulary.
What output does this skill produce?
An interactive HTML report written to a temp directory, with before/after diagrams, candidate refactors organized as cards, and a top recommendation. The skill then enters a grilling loop to design the deepened module if the user selects a candidate.
Does this skill automatically edit the codebase?
No. It explores, proposes candidates in a visual report, and then facilitates design conversation. Changes happen only after the user picks a candidate and decisions crystallize during the grilling loop.
Can this skill create or update CONTEXT.md and ADRs?
Yes, but only as side effects during the grilling loop: it adds new domain terms to CONTEXT.md as they emerge, and can record load-bearing rejections as ADRs if the user agrees the reasoning should guide future reviews.

Generated from the current SKILL.md. These answers refresh after source changes.