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python-code-reviewPython 代码审查

Agent Skill

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。它适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件、访问数据库或调用外部 API 时,应先明确运行目录和输入输出范围,避免误改生产数据。

总安装

9,102

周安装

387

GitHub Stars

54

下载量

3,189
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

3

许可证

MIT

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:python-code-review(Python 代码审查)
来源仓库:https://github.com/existential-birds/beagle
仓库路径:skills/python-code-review
安装命令:
npx skills add https://github.com/existential-birds/beagle --skill python-code-review
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/existential-birds/beagle --skill python-code-review

简介

执行深度 Python 代码审查与安全漏洞扫描。

  • 识别潜在 bug、性能瓶颈和架构缺陷。
  • 提供重构建议和单元测试补充方案。python-code-review 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 安装方式:通过 beagle 项目仓库部署代码审查能力。
  • 大规模项目审查前应划定代码变更范围。

SKILL.md

Python Code Review

Quick Reference

Issue TypeReference
Indentation, line length, whitespace, namingreferences/pep8-style.md
Missing/wrong type hints, Any usagereferences/type-safety.md
Blocking calls in async, missing awaitreferences/async-patterns.md
Bare except, missing context, loggingreferences/error-handling.md
Mutable defaults, print statementsreferences/common-mistakes.md

Review Checklist

PEP8 Style

  • 4-space indentation (no tabs)
  • Line length ≤79 characters (≤72 for docstrings/comments)
  • Two blank lines around top-level definitions, one within classes
  • Imports grouped: stdlib → third-party → local (blank line between groups)
  • No whitespace inside brackets or before colons/commas
  • Naming: snake_case for functions/variables, CamelCase for classes, UPPER_CASE for constants
  • Inline comments separated by at least two spaces

Type Safety

  • Type hints on all function parameters and return types
  • No Any unless necessary (with comment explaining why)
  • Proper T | None syntax (Python 3.10+)

Async Patterns

  • No blocking calls (time.sleep, requests) in async functions
  • Proper await on all coroutines

Error Handling

  • No bare except: clauses
  • Specific exception types with context
  • raise... from to preserve stack traces

Common Mistakes

  • No mutable default arguments
  • Using logger not print() for output
  • f-strings preferred over .format() or %

Valid Patterns (Do NOT Flag)

These patterns are intentional and correct - do not report as issues:

  • Type annotation vs type assertion - Annotations declare types but are not runtime assertions; don't confuse with missing validation
  • Using Any when interacting with untyped libraries - Required when external libraries lack type stubs
  • Empty __init__.py files - Valid for package structure, no code required
  • noqa comments - Valid when linter rule doesn't apply to specific case
  • Using cast() after runtime type check - Correct pattern to inform type checker of narrowed type

Context-Sensitive Rules

Only flag these issues when the specific conditions apply:

IssueFlag ONLY IF
Generic exception handlingSpecific exception types are available and meaningful
Unused variablesVariable lacks _ prefix AND isn't used in f-strings, logging, or debugging

When to Load References

  • Reviewing code formatting/style → pep8-style.md
  • Reviewing function signatures → type-safety.md
  • Reviewing async def functions → async-patterns.md
  • Reviewing try/except blocks → error-handling.md
  • General Python review → common-mistakes.md

Review Questions

  1. Does the code follow PEP8 formatting (indentation, line length, whitespace)?
  2. Are imports properly grouped (stdlib → third-party → local)?
  3. Do names follow conventions (snake_case, CamelCase, UPPER_CASE)?
  4. Are all function signatures fully typed?
  5. Are async functions truly non-blocking?
  6. Do exceptions include meaningful context?
  7. Are there any mutable default arguments?

Before Submitting Findings

Load and follow review-verification-protocol before reporting any issue.

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

04

需要参考平台分布和安装热度时

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

补充不同宿主或平台的使用分布数据

能力 5

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

Claude Code

26.22%
按下载量换算836

Gemini CLI

24.98%
按下载量换算797

Antigravity

16.95%
按下载量换算541

Cursor

13.03%
按下载量换算416

OpenCode

8.23%
按下载量换算262

github-copilot

3.37%
按下载量换算107

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。

来源信息

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