New: 97,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Official agent skill

Improve Codebase Architecture

by sanity-io in sanity-io/sanity

Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules.

OfficialMITAuto-check passedDevelopment

Install Improve Codebase Architecture

skills CLI
$ npx skills add sanity-io/sanity --skill improve-codebase-architecture -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sanity-io/sanity improve-codebase-architecture --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sanity-io/sanity.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/improve-codebase-architecture .claude/skills/improve-codebase-architecture && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
improve-codebase-architecture
GitHub stars
6.4k
Used in
3 other repos
Token cost
~1k tokens
SKILL.md length
548 words
Files
2
Skills in repo
34
Repo updated
First seen
Licence
MIT

At a glance

Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules.

  • Works in 7 steps: Explore the codebase → Present candidates → User picks a candidate → …
  • User wants to improve architecture
  • Calls gh
  • Find refactoring opportunities

What it does

Improve Codebase Architecture is an agent skill from sanity-io/sanity, published by the product's own GitHub organization. Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules. Use when user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more AI-navigable.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `REFERENCE.md`).

It sits in Development, covering Refactoring. The repository describes itself as: Sanity Studio – Rapidly configure content workspaces powered by structured content. The licence is MIT.

When your agent uses it

  • User wants to improve architecture
  • Find refactoring opportunities
  • Consolidate tightly-coupled modules
  • Make a codebase more AI-navigable

Example prompts

  • “/improve-codebase-architecture”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Explore the codebase
  2. Present candidates
  3. User picks a candidate
  4. Frame the problem space
  5. Design multiple interfaces
  6. User picks an interface (or accepts recommendation)
  7. Create GitHub issue

What it can do on your machine

Read from SKILL.md and the folder at commit 982525c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gh

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gh, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Improve Codebase Architecture loads about 1k tokens when it runs. Until then it costs about 82 tokens; SKILL.md has 548 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~82
When it runs · the whole SKILL.md, loaded when a task matches
~1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sanity-io/sanity at commit 982525c, republished under its MIT licence (© sanity-io). 548 words, ~1,025 tokens.

Download SKILL.mdSave it as .claude/skills/improve-codebase-architecture/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
improve-codebase-architecture
description
Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules. Use when user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more AI-navigable.

Improve Codebase Architecture

Explore a codebase like an AI would, surface architectural friction, discover opportunities for improving testability, and propose module-deepening refactors as GitHub issue RFCs.

A deep module (John Ousterhout, "A Philosophy of Software Design") has a small interface hiding a large implementation. Deep modules are more testable, more AI-navigable, and let you test at the boundary instead of inside.

Process

1. Explore the codebase

Use the Agent tool with subagent_type=Explore to navigate the codebase naturally. Do NOT follow rigid heuristics — explore organically and note where you experience friction:

  • Where does understanding one concept require bouncing between many small files?
  • Where are modules so shallow that the interface is 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?
  • Where do tightly-coupled modules create integration risk in the seams between them?
  • Which parts of the codebase are untested, or hard to test?

The friction you encounter IS the signal.

2. Present candidates

Present a numbered list of deepening opportunities. For each candidate, show:

  • Cluster: Which modules/concepts are involved
  • Why they're coupled: Shared types, call patterns, co-ownership of a concept
  • Dependency category: See REFERENCE.md for the four categories
  • Test impact: What existing tests would be replaced by boundary tests

Do NOT propose interfaces yet. Ask the user: "Which of these would you like to explore?"

3. User picks a candidate
4. Frame the problem space

Before spawning sub-agents, write a user-facing explanation of the problem space for the chosen candidate:

  • The constraints any new interface would need to satisfy
  • The dependencies it would need to rely on
  • A rough illustrative code sketch to make the constraints concrete — this is not a proposal, just a way to ground the constraints

Show this to the user, then immediately proceed to Step 5. The user reads and thinks about the problem while the sub-agents work in parallel.

Show full SKILL.md (230 more words)Show less
5. Design multiple interfaces

Spawn 3+ sub-agents in parallel using the Agent tool. Each must produce a radically different interface for the deepened module.

Prompt each sub-agent with a separate technical brief (file paths, coupling details, dependency category, what's being hidden). This brief is independent of the user-facing explanation in Step 4. Give each agent a different design constraint:

  • Agent 1: "Minimize the interface — aim for 1-3 entry points max"
  • Agent 2: "Maximize flexibility — support many use cases and extension"
  • Agent 3: "Optimize for the most common caller — make the default case trivial"
  • Agent 4 (if applicable): "Design around the ports & adapters pattern for cross-boundary dependencies"

Each sub-agent outputs:

  1. Interface signature (types, methods, params)
  2. Usage example showing how callers use it
  3. What complexity it hides internally
  4. Dependency strategy (how deps are handled — see REFERENCE.md)
  5. Trade-offs

Present designs sequentially, then compare them in prose.

After comparing, give your own recommendation: which design you think is strongest and why. If elements from different designs would combine well, propose a hybrid. Be opinionated — the user wants a strong read, not just a menu.

6. User picks an interface (or accepts recommendation)
7. Create GitHub issue

Create a refactor RFC as a GitHub issue using gh issue create. Use the template in REFERENCE.md. Do NOT ask the user to review before creating — just create it and share the URL.

© sanity-io, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in .agents/skills/improve-codebase-architecture of sanity-io/sanity.

  • SKILL.md
  • REFERENCE.md

Open the folder on GitHubat commit 982525c

Used in 3 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in sanity-io/sanity, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Improve Codebase Architecture next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Improve Codebase Architecture compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Improve Codebase Architecture this skillsanity-io/sanity6.4k3 repos~1kAutomated safety check: PassMIT
Guidelinesakash-network/node1.1k22 repos~577Automated safety check: PassMIT
Component Refactoringlangflow-ai/langflow156k—~3.5kAutomated safety check: PassMIT
Migrate Core Code to Submodulestinyhumansai/openhuman41k—~2.6kAutomated safety check: PassGPL-3.0
ast-grep Structural Searchcode-yeongyu/oh-my-openagent70k—~3.3kAutomated safety check: PassMIT
Systematic Code Refactoringluongnv89/claude-howto42k—~3kAutomated safety check: PassMIT

Similar skills

  • Guidelines

    akash-network/node

    Behavioral guidelines to reduce common LLM coding mistakes. An agent skill from akash-network/node.

    1.1k GitHub starsUsed in 22 repos~577 tokens
    DevelopmentAuto-check passed

  • Component Refactoring

    langflow-ai/langflow

    Refactor high-complexity React components in Langflow frontend.

    156k GitHub stars~3.5k tokensUpdated today
    DevelopmentAuto-check passed

  • Migrate Core Code to Submodules

    tinyhumansai/openhuman

    Plans and carries out moving non-host-specific code and its tests from the OpenHuman core into vendored tiny submodule libraries, then releases the submodule and re-pins the host.

    41k GitHub stars~2.6k tokensUpdated today
    DevelopmentAuto-check passed

  • ast-grep Structural Search

    code-yeongyu/oh-my-openagent

    Searches and rewrites code by syntax-tree shape across 25 languages with ast-grep, for codemods, structural queries and YAML lint rules, using a Python wrapper script.

    70k GitHub stars~3.3k tokensUpdated today
    DevelopmentAuto-check passed

  • Systematic Code Refactoring

    luongnv89/claude-howto

    Guides refactoring in phases based on Martin Fowler's method: research, test coverage check, planning and small tested steps, with your approval at each phase.

    42k GitHub stars~3k tokensUpdated 7 days ago
    DevelopmentAuto-check passed

  • Codex

    skills-directory/skill-codex

    A skill your agent uses when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing

    1.5k GitHub starsUsed in 3 repos~1.8k tokens
    DevelopmentAuto-check passed

More from sanity-io/sanity

All 34 skills in this repo

  • Playwright CLI

    sanity-io/sanity

    Official

    Automates browser interactions for web testing, form filling, screenshots, and data extraction.

    6.4k GitHub starsUsed in 18 repos~1.9k tokens
    Auto-check passed

  • Find Skills

    sanity-io/sanity

    Official

    Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities.

    6.4k GitHub starsUsed in 67 repos~1.2k tokens
    Auto-check passed

  • Vercel React Best Practices

    sanity-io/sanity

    Official

    React and Next.js performance optimization guidelines from Vercel Engineering.

    6.4k GitHub starsUsed in 130 repos~1.6k tokens
    Auto-check passed

  • Before And After

    sanity-io/sanity

    Official

    Add existing screenshots or screen recordings to a GitHub pull request as a before/after or preview block.

    6.4k GitHub starsUsed in 1 repo~2.1k tokens
    Auto-check passed

  • React Devtools

    sanity-io/sanity

    Official

    React DevTools CLI for AI agents. An agent skill from sanity-io/sanity.

    6.4k GitHub starsUsed in 3 repos~2.1k tokens
    Auto-check passed

  • TDD

    sanity-io/sanity

    Official

    Test-driven development with red-green-refactor loop. An agent skill from sanity-io/sanity.

    6.4k GitHub starsUsed in 20 repos~1k tokens
    Auto-check passed

Categories

Questions about Improve Codebase Architecture

What does Improve Codebase Architecture do?

Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules. Improve Codebase Architecture is an agent skill from sanity-io/sanity, published by the product's own GitHub organization. Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules.

When should I use Improve Codebase Architecture?

Improve Codebase Architecture fits situations like: user wants to improve architecture; find refactoring opportunities; consolidate tightly-coupled modules; make a codebase more AI-navigable.

How do I install Improve Codebase Architecture in Claude Code?

Run `npx skills add sanity-io/sanity --skill improve-codebase-architecture -a claude-code`. Or copy the skill folder (.agents/skills/improve-codebase-architecture in sanity-io/sanity) into .claude/skills/improve-codebase-architecture in your project. Claude Code loads it when a task matches its description.

How do I install Improve Codebase Architecture in Codex?

Run `npx skills add sanity-io/sanity --skill improve-codebase-architecture -a codex`. Or copy the skill folder (.agents/skills/improve-codebase-architecture in sanity-io/sanity) into .agents/skills/improve-codebase-architecture in your project. Codex loads it when a task matches its description.

Can I use Improve Codebase Architecture in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sanity-io/sanity --skill improve-codebase-architecture -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/improve-codebase-architecture, .gemini/skills/improve-codebase-architecture, .github/skills/improve-codebase-architecture and .opencode/skills/improve-codebase-architecture in your project.

What does Improve Codebase Architecture need to run?

Going by SKILL.md and its folder, Improve Codebase Architecture needs the command-line tools its instructions call (gh).

Does Improve Codebase Architecture access the network?

SKILL.md contains no URLs. Its commands use gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Improve Codebase Architecture safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Improve Codebase Architecture use?

Improve Codebase Architecture is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Improve Codebase Architecture use?

About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Improve Codebase Architecture?

Skills that share tags, products or a category with Improve Codebase Architecture: Guidelines (akash-network/node, 1.1k stars), Component Refactoring (langflow-ai/langflow, 156k stars), Migrate Core Code to Submodules (tinyhumansai/openhuman, 41k stars) and ast-grep Structural Search (code-yeongyu/oh-my-openagent, 70k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Improve Codebase Architecture?

sanity-io (a GitHub organization, an official publisher) maintains it in sanity-io/sanity, which has 6,352 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on October 7, 2026.

Source: sanity-io/sanity on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.