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python-standardsPython standards 测试

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

519

周安装

21

GitHub Stars

23

下载量

163
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:python-standards(Python standards 测试)
来源仓库:https://github.com/akaszubski/autonomous-dev
仓库路径:skills/python-standards
安装命令:
npx skills add https://github.com/akaszubski/autonomous-dev --skill python-standards
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/akaszubski/autonomous-dev --skill python-standards

简介

定义 Python 项目的质量标准,包括 PEP8、Black 格式化与类型提示规范。

  • 适用于代码生成、格式化和依赖管理,强调公共函数必须带类型注解。
  • 使用时需配合 isort 和 Black 自动格式化,确保导入排序一致。
  • 安装命令:npx skills add https://github.com/akaszubski/autonomous-dev --skill python-standards
  • 建议确认虚拟环境与依赖版本后再执行脚本。

SKILL.md

Python Standards Skill

Python code quality standards for autonomous-dev project.

When This Activates

  • Writing Python code
  • Code formatting
  • Type hints
  • Docstrings
  • Keywords: "python", "format", "type", "docstring"

Code Style (PEP 8 + Black)

SettingValue
Line length100 characters
Indentation4 spaces (no tabs)
QuotesDouble quotes
ImportsSorted with isort
black --line-length=100 src/ tests/
isort --profile=black --line-length=100 src/ tests/

Type Hints (Required)

Rule: All public functions must have type hints on parameters and return.

def process_file(
    input_path: Path,
    output_path: Optional[Path] = None,
    *,
    max_lines: int = 1000
) -> Dict[str, any]:
    """Type hints on all parameters and return."""
    pass

Docstrings (Google Style)

Rule: All public functions/classes need docstrings with Args, Returns, Raises.

def process_data(data: List[Dict], *, batch_size: int = 32) -> ProcessResult:
    """Process data with validation.

    Args:
        data: Input data as list of dicts
        batch_size: Items per batch (default: 32)

    Returns:
        ProcessResult with items and metrics

    Raises:
        ValueError: If data is empty
    """

Error Handling

Rule: Error messages must include context + expected + docs link.

# ✅ GOOD
raise FileNotFoundError(
    f"Config file not found: {path}\n"
    f"Expected: YAML with keys: model, data\n"
    f"See: docs/guides/configuration.md"
)

# ❌ BAD
raise FileNotFoundError("File not found")

Exception Hierarchy

Define a project-level exception hierarchy for structured error handling:

class AppError(Exception):
    """Base exception for the application."""
    pass

class ConfigError(AppError):
    """Configuration loading or validation error."""
    pass

class ValidationError(AppError):
    """Input or data validation error."""
    pass

class ExternalServiceError(AppError):
    """Error communicating with external service."""
    pass

When to use custom vs built-in exceptions:

  • Use built-in (ValueError, TypeError, FileNotFoundError) for standard programming errors
  • Use custom exceptions when callers need to catch specific application-level failures
  • Always inherit from a project base exception for catch-all handling

Error Message Format

Every error message should follow this three-part format:

  1. Context - What happened and where
  2. Expected - What was expected instead
  3. Docs link - Where to find more information
raise ValidationError(
    f"Invalid config key '{key}' in {config_path}\n"
    f"Expected one of: {', '.join(valid_keys)}\n"
    f"See: docs/configuration.md#valid-keys"
)

Graceful Degradation

When a non-critical operation fails, log and continue rather than crashing:

try:
    optional_result = enhance_with_cache(data)
except CacheError:
    logging.warning("Cache unavailable, proceeding without cache")
    optional_result = None

Naming Conventions

TypeConventionExample
ClassesPascalCaseModelTrainer
Functionssnake_casetrain_model()
ConstantsUPPER_SNAKEMAX_LENGTH
Private_underscore_helper()

Best Practices

  1. Keyword-only args - Use * for clarity
  2. Pathlib - Use Path not string paths
  3. Context managers - Use with for resources
  4. Dataclasses - For configuration objects
# Keyword-only args
def train(data: List, *, learning_rate: float = 1e-4):
    pass

# Pathlib
config = Path("config.yaml").read_text()

Code Quality Commands

flake8 src/ --max-line-length=100       # Linting
mypy src/[project_name]/                # Type checking
pytest --cov=src --cov-fail-under=80    # Coverage

Key Takeaways

  1. Type hints - Required on all public functions
  2. Docstrings - Google style, with Args/Returns/Raises
  3. Black formatting - 100 char line length
  4. isort imports - Sorted and organized
  5. Helpful errors - Context + expected + docs link
  6. Pathlib - Use Path not string paths
  7. Keyword args - Use * for clarity
  8. Dataclasses - For configuration objects

Related Skills

  • testing-guide - Testing patterns and TDD methodology
  • error-handling-patterns - Error handling best practices

Hard Rules

FORBIDDEN:

  • Public functions without type hints on parameters and return values
  • Bare except: or except Exception: without re-raising or specific handling
  • Mutable default arguments (def f(items=[]))
  • Using os.path when pathlib.Path is available

REQUIRED:

  • All public APIs MUST have Google-style docstrings with Args/Returns/Raises
  • All code MUST pass black formatting (100 char line length)
  • Imports MUST be sorted with isort (profile=black)
  • Keyword-only arguments MUST be used for functions with 2+ optional parameters

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

32.96%
按下载量换算54

Claude

32.6%
按下载量换算53

Cursor

20.54%
按下载量换算33

Gemini CLI

9.48%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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