kb: Skill for Claude Code

.agents/skills/improve-codebase-architecture/SKILL.md

improve-codebase-architecture is a skill for Claude Code, Codex from compozy/kb. It costs 32 tokens per session (1,342 once invoked), scanned A, a copy of improve-codebase-architecture, MIT.

A workflow that scans a codebase for architectural friction and presents possible refactors in an HTML report. It uses the idea of deep modules: code that hides substantial behaviour behind a small interface.

In plain words
What is it for?
Use it to find modules that are hard to change or test, propose cleaner seams, review recent problem areas, and discuss a chosen architecture refactor.
Why use it?
It turns vague structural problems into specific improvement options while keeping the review focused on the parts of the codebase that matter. It also provides a process for examining and challenging one selected improvement.

Skill for Claude CodeCodex

Written for Claude Code and Codex: disable-model-invocation in frontmatter, but also agents/openai.yaml present. Also seen: mentions subagents; installed under .agents/ (shared by several agents).

This is compozy/kb's own configuration. It tells Claude Code and Codex how to work on kb itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything kb configures →

View source ↗ compozy/kb
Reuse

Borrowing it

Nothing to install: this file belongs to compozy/kb. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/compozy/kb/main/.agents/skills/improve-codebase-architecture/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/compozy/kb

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for improve-codebase-architecture

README.md
[![agentmods](https://agentmods.dev/badge/skills/compozy/kb/improve-codebase-architecture/github.svg)](https://agentmods.dev/skills/compozy/kb/improve-codebase-architecture)
Your own site
<a href="https://agentmods.dev/skills/compozy/kb/improve-codebase-architecture"><img src="https://agentmods.dev/badge/skills/compozy/kb/improve-codebase-architecture/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for improve-codebase-architecture

Your own site · 80×15
<a href="https://agentmods.dev/skills/compozy/kb/improve-codebase-architecture"><img src="https://agentmods.dev/badge/skills/compozy/kb/improve-codebase-architecture.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,342 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.01342
Opus 5.5 $0.00013 $0.00537
Sonnet 5.5 $0.00006 $0.00268
Haiku 4.5 $0.00003 $0.00134

Measured 25d ago against content hash d1ac25511a93, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

improve-codebase-architecture scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 25d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to improve-codebase-architecture — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/improve-codebase-architecture/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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?

Read the full file on GitHub · 72 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 25d ago First seen · 72 lines · 32 tokens per session scan A d1ac25511a93

Subscribe to this mod's changes

improve-codebase-architecture is a skill published in the GitHub repository compozy/kb (112 stars, last pushed 3d ago), licensed MIT. It adds 32 tokens to every session and 1,342 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to improve-codebase-architecture, differing in 10 lines, and is treated as a copy.

Related

Other skills, from other repositories

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens