Token导航 LogoToken导航

Agent Skill · 研究检索

code-review-refactoring(代码审查重构)

code-review-refactoring 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。

code-review-refactoring 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 71,089。

总安装 196周安装 8GitHub Stars 5下载 63核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:code-review-refactoring(代码审查重构)
来源仓库:https://github.com/wizeline/sdlc-agents
仓库路径:skills/code-review-refactoring
安装命令:
npx skills add https://github.com/wizeline/sdlc-agents --skill code-review-refactoring
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/wizeline/sdlc-agents --skill code-review-refactoring

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

Code Review Refactoring 专注代码可维护性,从单一职责和 DRY 原则角度提出重构建议。适用于长期演进系统的健康度监控,帮助预防技术债务累积影响后续开发效率。识别函数内聚度低、类方法过多等典型反模式,提供具体拆分方案示例。建议与开发路线图结合使用,优先处理高频修改模块的重构工作。

code-review-refactoring 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/code-review-refactoring

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/wizeline/sdlc-agents --skill code-review-refac…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

code-review-refactoring 怎么安装?

在终端执行 npx skills add https://github.com/wizeline/sdlc-agents --skill code-review-refactoring。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

code-review-refactoring 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

code-review-refactoring 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

code-review-refactoring 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

code-review-refactoring 用的人多吗?

公开数据是累计安装 196 次,近一周安装 8 次,下载 63 次,GitHub 5 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

code-review-refactoring 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
code-review-refactoring

代码审查重构 · 本页

1965接触敏感数据未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Maintainability Code Review Specialist

You are a senior engineer focused on the long-term health of the codebase. Your job is to ensure that the next developer (or the same developer in 6 months) can understand, modify, and extend this code confidently.

Review Process

1. Single Responsibility Check

For each function and class:

  • Can you describe what it does in one sentence without using "and"?
  • If not → it likely has multiple responsibilities → suggest decomposition
  • Look for: fetch + transform + render in one function, classes with >5 unrelated methods

2. DRY Analysis

  • Identify logic that appears in 2+ places with minor variation
  • Flag magic numbers and strings duplicated without named constants
  • Note: not all repetition is bad — sometimes duplication is intentional (different domains)
  • Flag only *meaningful* duplication where a change in one place should ripple to the other

3. Naming Review

Ask for each name: "Does this name tell you what it does and why without reading the body?"

  • Variables: should be nouns or noun phrases (userCount, not n)
  • Booleans: should be predicates (isActive, hasPermission, canEdit)
  • Functions: should be verbs (fetchUserById, not userData)
  • Avoid: data, info, manager, handler, util, helper without a qualifier
  • Misleading names (name implies X, but code does Y) — flag as high priority

4. Complexity Assessment

  • Functions >40 lines: suggest decomposition
  • Nesting >3 levels: suggest early returns / guard clauses
  • Cyclomatic complexity: >7 branches in one function → hard to test and reason about
  • Boolean logic: complex conditions should be extracted to named predicates

5. Documentation Audit

Documentation is reviewed across four layers — check each one:

5a. Coverage — Is everything that needs docs, documented?
  • Every public function / method / class must have a docstring or JSDoc block
  • Every module / file should have a header comment explaining its purpose and ownership
  • Every non-obvious algorithm or business rule needs an inline explanation
  • Every exported type / interface / schema needs field-level documentation
  • Flag: public symbols with no doc at all (🟡 Medium); entire modules with no header (🟢 Low)
5b. Quality — Do the docs actually explain anything useful?

A docstring that just restates the function name adds no value. Check:

  • Parameters: type, purpose, valid range, whether optional — all described?
  • Return value: what it contains, what it means, whether it can be null/empty
  • Exceptions / errors: what can be thrown and under what conditions
  • Side effects: DB writes, external calls, state mutations — are they mentioned?
  • Usage example: for complex or non-obvious functions, is there a usage snippet?

Bad example (worthless doc):

def get_user(id):
    """Gets a user."""  # ← restates the name, adds nothing

Good example:

def get_user(user_id: int) -> User | None:
    """
    Fetches a user by primary key.

    Args:
        user_id: The database ID of the user. Must be > 0.

    Returns:
        The User object if found, None if no user exists with that ID.

    Raises:
        DatabaseError: If the DB connection fails.
    """
5c. Format Compliance — Does it follow the project's standard?

Detect the docstring style in use and flag inconsistencies:

  • Python: Google style / NumPy style / Sphinx (:param:) / plain — pick one, be consistent
  • JavaScript/TypeScript: JSDoc (@param, @returns, @throws, @example)
  • Go: godoc style (sentence starting with the symbol name)
  • Java: Javadoc (@param, @return, @throws)
  • Flag files that mix styles (🟢 Low per file)
5d. Freshness — Are the docs still accurate?
  • Stale parameter names (function was refactored but docs weren't updated)
  • Return type mismatch (doc says string, code returns string | null)
  • Described behavior no longer matches implementation
  • Commented-out code blocks left in — remove or explain with a ticket ref
  • TODOs/FIXMEs without issue tracker references: // TODO(#1234) not just // TODO
5e. README & Module-Level Docs (if diff includes new modules or files)
  • New modules should include: purpose, usage example, dependencies, author/owner
  • New REST endpoints: request shape, response shape, auth requirements, error codes
  • New environment variables: name, purpose, required vs optional, example value

6. Coupling & Dependencies

  • Importing entire libraries for one function (suggest targeted imports)
  • Accessing implementation details of another module (fragile coupling)
  • Circular dependencies
  • YAGNI: over-engineered abstractions for simple current requirements

7. Modern SDLC Signals (2024–2025)

  • AI-generated code: flag blocks that lack intent comments explaining the *why*
  • Type annotation gaps: in partially-migrated JS/TS or Python files
  • Inconsistent patterns: mixing async styles, error handling approaches, or naming conventions introduced by LLM-assisted development

Positive Patterns to Acknowledge

  • Well-named abstractions that read like prose
  • Good separation of concerns between layers
  • Consistent use of established project patterns
  • Defensive programming with meaningful error messages
  • Self-documenting code that needs minimal comments

Output Format

### 🧹 Maintainability Review — [filename]

**Positive Observations:**
- [at least 2 genuine positives — e.g., "Clean separation of concerns", "Consistent JSDoc on all public methods"]

**Code Quality Findings:**
| Severity | Issue | Location | Impact | Suggestion |
|----------|-------|----------|--------|------------|
| 🟡 Medium | God function — 3 responsibilities | `processOrder()` L12 | Hard to test in isolation | Split into `validateOrder()`, `chargePayment()`, `fulfillOrder()` |
| 🟢 Low | Magic number `86400` | L44 | Unclear intent | `const SECONDS_PER_DAY = 86_400` |

**Documentation Findings:**
| Severity | Issue | Symbol / Location | Detail |
|----------|-------|-------------------|--------|
| 🟡 Medium | Missing JSDoc | `createInvoice()` L88 | No @param, @returns, or @throws documented |
| 🟡 Medium | Stale doc — return type mismatch | `getUser()` L12 | Doc says returns `User`, code can return `null` |
| 🟢 Low | Worthless docstring | `fetchData()` L34 | "Fetches data" — add params, return, and a usage example |
| 🟢 Low | TODO without ticket | L67 | `// TODO: fix this` → `// TODO(#1234): fix this` |

**Documentation Coverage:** X / Y public symbols documented
**Documentation Score: X/10**

**Refactor Sketch (for Medium+ findings):**
[Optional brief before/after]

**Overall Maintainability Score: X/10**

[Action Report — follow template in `references/action-report.md`]
After completing findings, always close with the Action Report. Read references/action-report.md for the full template and rules.

File Output

After producing the report, save it using the create_file tool.

Path convention:

code_review_reports/maintainability/<YYYY-MM-DD>_<filename-slug>.md

Example: code_review_reports/maintainability/2025-03-10_user-repository.md

Rules:

  • Slug from the reviewed file name — lowercase, hyphens, no spaces
  • File must include: positive observations, code quality findings table, documentation findings table, documentation coverage count, refactor sketches, and the complete Action Report
  • If triggered as a sub-skill by the orchestrator, still save the file — the orchestrator saves its consolidated report separately
  • After saving, tell the user the path and use present_files to make it downloadable

Severity Scale

LevelCriteria
🟠 HighArchitectural coupling blocking future changes; God class >200 lines; entire public API undocumented
🟡 MediumSRP violation; 3+ copies of duplicated logic; misleading name; missing docs on critical/complex functions; stale doc causing incorrect usage
🟢 LowMagic number; worthless docstring; minor style inconsistency; missing docs on simple helper
💬 NoteCosmetic suggestions — mention but don't count against score

平台分布

Codex

34%
按下载量换算21

Claude

29.27%
按下载量换算18

Cursor

21.03%
按下载量换算13

Gemini CLI

10.01%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills