Agent Skillssanity-io/sanity › improve-codebase-architecture

improve-codebase-architecture

GitHub

探索代码库以发现架构改进机会,识别耦合模块和可测试性提升点。通过分析模块深度、依赖关系和测试影响,提出重构建议并生成接口设计 RFC,旨在使代码更易于维护和AI导航。

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

Trigger Scenarios

用户希望改进代码架构 寻找重构机会 整合紧密耦合的模块 提高代码库的可测试性

Install

npx skills add sanity-io/sanity --skill improve-codebase-architecture -g -y
More Options

Non-standard path

npx skills add https://github.com/sanity-io/sanity/tree/main/.agents/skills/improve-codebase-architecture -g -y

Use without installing

npx skills use sanity-io/sanity@improve-codebase-architecture

指定 Agent (Claude Code)

npx skills add sanity-io/sanity --skill improve-codebase-architecture -a claude-code -g -y

安装 repo 全部 skill

npx skills add sanity-io/sanity --all -g -y

预览 repo 内 skill

npx skills add sanity-io/sanity --list

SKILL.md

Frontmatter
{
    "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.

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.

Version History

  • 3235fb3 Current 2026-08-20 10:56

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