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improve-codebase-architecture改进代码库架构

Agent Skill

improve-codebase-architecture 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

269

周安装

11

GitHub Stars

14

下载量

87
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:improve-codebase-architecture(改进代码库架构)
来源仓库:https://github.com/bahayonghang/my-claude-code-settings
仓库路径:skills/improve-codebase-architecture
安装命令:
npx skills add https://github.com/bahayonghang/my-claude-code-settings --skill improve-codebase-architecture
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/bahayonghang/my-claude-code-settings --skill improve-codebase-architecture

简介

improve-codebase-architecture 识别高摩擦架构区域并提出深度模块优化建议。

  • 优先小接口隐藏复杂实现,强化可维护性与扩展性。
  • 结合 deepening-guide.md 判断依赖关系与测试策略合理性。
  • 输出聚焦具体路径,避免全局重构带来的过度风险。
  • 建议配合子代理并行探索多个候选改进点。

SKILL.md

Improve Codebase Architecture

Find architectural friction the way a future maintainer or coding agent experiences it. Favor deep modules: a small interface hiding substantial implementation complexity.

Read $SKILL_DIR/references/deepening-guide.md before classifying dependencies, judging test strategy, or drafting the RFC.

Workflow

  1. Decide scope. If the user gives a path, subsystem, ticket, or architectural theme, stay inside it. Otherwise explore until you can name the highest-friction areas.
  2. Explore the codebase using whatever discovery tools are available.

- If subagents are available, you may run one exploration pass and 2-4 design passes in parallel. - If subagents are unavailable, do the same work sequentially. Do not fail just because parallelism is unavailable. - Treat friction as evidence: cross-file bouncing, redundant adapters, shallow modules, hidden orchestration, and tests that protect internals instead of behavior.

  1. Surface 3-5 candidate deepening opportunities. For each candidate, report:

- Cluster - Why they're coupled - Dependency category - Test impact - Expected leverage - Migration cost / risk - Confidence

  1. If no candidate is strong enough, say so explicitly and stop. Do not invent an RFC just to satisfy the workflow.
  2. Ask the user which candidate to explore. If the user only wanted an architectural review, stop after the candidate list and recommendation.
  3. Frame the problem space for the chosen candidate before proposing an interface:

- Constraints the new interface must satisfy - Dependencies it must rely on - Non-goals - Likely failure modes - A rough illustrative code sketch that grounds the constraints without committing to a design

  1. Design 2-4 materially different interfaces.

- With subagents: give each one a distinct design goal. - Without subagents: produce the same diversity of designs yourself, one by one. - Useful design goals: - Minimize interface surface - Optimize for common caller ergonomics - Maximize extension flexibility - Isolate cross-boundary dependencies with ports and adapters

  1. For each design, include:

1. Interface signature 2. Usage example 3. Complexity hidden internally 4. Dependency strategy 5. Trade-offs 6. Failure modes 7. Migration shape

  1. Compare the designs in prose, then give a clear recommendation. If a hybrid is best, say exactly which parts should be combined.
  2. Draft the RFC as Markdown using the template in $SKILL_DIR/references/deepening-guide.md.
  3. Save the draft locally as ./architecture-rfc-<candidate-slug>.md.
  4. Only create a GitHub issue if all of these are true:
  • The user explicitly asks for an issue
  • gh is installed and authenticated
  • The draft is already complete Otherwise, return the Markdown draft and the suggested gh issue create next step without executing it.

Working heuristics

  • Prefer seams where the bugs live in orchestration, not in leaf helpers.
  • Prefer module boundaries that let tests assert observable behavior instead of call order or internal state.
  • Prefer designs that reduce navigation cost for both humans and agents.
  • Be suspicious of "extract function for testability" if the real coupling stayed in the caller.
  • Do not let current file layout dictate the future interface.

Output contract

When presenting candidate opportunities, always include:

  • Cluster
  • Why they're coupled
  • Dependency category
  • Test impact
  • Expected leverage
  • Migration cost / risk
  • Confidence

When presenting the final recommendation, always include:

  • The chosen design or hybrid
  • Why it wins
  • What should remain outside the module
  • Which existing tests become redundant
  • Which new boundary tests matter most

Failure handling

  • If dependency classification is uncertain, name the uncertainty and what evidence is missing.
  • If the codebase is too large, narrow scope before claiming confidence.
  • If the best answer is "leave this area alone for now," say that plainly.
  • Never mutate remote systems by default. Draft first, publish second.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.9%
按下载量换算29

Claude

31.61%
按下载量换算28

Cursor

20.48%
按下载量换算18

Gemini CLI

9.46%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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