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python-workspacePython workspace 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

1,958

周安装

80

GitHub Stars

38

下载量

627
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-workspace(Python workspace 测试)
来源仓库:https://github.com/terrylica/cc-skills
仓库路径:skills/python-workspace
安装命令:
npx skills add https://github.com/terrylica/cc-skills --skill python-workspace
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/terrylica/cc-skills --skill python-workspace

简介

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。

  • 适合让 Agent 阅读 Python 代码、定位测试问题或生成脚本。
  • 使用时需确认项目虚拟环境、依赖版本和测试入口,避免误改生产数据。
  • 安装方式:通过 npx skills add 从指定 GitHub 仓库添加。
  • 涉及执行脚本或访问数据库时,应先明确运行目录和输入输出范围。

SKILL.md

MQL5-Python Translation Workspace Skill

Seamless MQL5 indicator translation to Python with autonomous validation and self-correction.


Self-Evolving Skill: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.

When to Use This Skill

Use this skill when the user wants to:

  • Export market data or indicator values from MetaTrader 5
  • Translate MQL5 indicators to Python implementations
  • Validate Python indicator accuracy against MQL5 reference
  • Understand MQL5-Python workflow capabilities and limitations
  • Troubleshoot common translation issues

Activation Phrases: "MQL5", "MetaTrader", "indicator translation", "Python validation", "export data", "mql5-crossover workspace"


Core Mission

Main Theme: Make MQL5-Python translation as seamless as possible through:

  1. Autonomous workflows (headless export, CLI compilation, automated validation)
  2. Validation-driven iteration (>=0.999 correlation gates all work)
  3. Self-correction (documented failures prevent future mistakes)
  4. Clear boundaries (what works vs what doesn't, with alternatives)

Project Root: ~/Library/Application Support/CrossOver/Bottles/MetaTrader 5/drive_c


Workspace Capabilities Matrix

WHAT THIS WORKSPACE CAN DO

1. Automated Headless Market Data Export (v3.0.0)

Status: PRODUCTION (0.999920 correlation validated)

What It Does:

  • Fetches OHLCV data + built-in indicators (RSI, SMA) from any symbol/timeframe
  • True headless via Wine Python + MetaTrader5 API
  • No GUI initialization required (cold start supported)
  • Execution time: 6-8 seconds for 5000 bars

Command Example:

CX_BOTTLE="MetaTrader 5" \
WINEPREFIX="$HOME/Library/Application Support/CrossOver/Bottles/MetaTrader 5" \
wine "C:\\Program Files\\Python312\\python.exe" \
  "C:\\users\\crossover\\export_aligned.py" \
  --symbol EURUSD --period M1 --bars 5000

Use When: User needs automated market data exports without GUI interaction

Limitations: Cannot access custom indicator buffers (API restriction)

Reference: /docs/guides/WINE_PYTHON_EXECUTION.md


Reference Documentation

For detailed information, see:


Troubleshooting

IssueCauseSolution
Wine Python not foundCrossOver/Wine not installedInstall CrossOver, verify bottle path
MT5 API connection failedMetaTrader not runningLaunch MetaTrader 5 before running export
Correlation below 0.999Indicator mismatchVerify warmup periods, check calculation alignment
Custom indicator not workingAPI restrictionUse CSV export from MT5, not Python API
UnicodeDecodeErrorWindows path encodingUse raw strings for Windows paths in Wine
Symbol not foundWrong symbol formatUse exact MT5 symbol name (e.g., EURUSD not EUR/USD)
Timeout on exportToo many bars requestedReduce bar count, default 5000 is safe
Permission deniedWine prefix incorrectSet WINEPREFIX to correct CrossOver bottle path

Post-Execution Reflection

After this skill completes, check before closing:

  1. Did the command succeed? — If not, fix the instruction or error table that caused the failure.
  2. Did parameters or output change? — If the underlying tool's interface drifted, update Usage examples and Parameters table to match.
  3. Was a workaround needed? — If you had to improvise (different flags, extra steps), update this SKILL.md so the next invocation doesn't need the same workaround.

Only update if the issue is real and reproducible — not speculative.

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

25.37%
按下载量换算159

OpenCode

23.17%
按下载量换算145

Antigravity

17.67%
按下载量换算111

Gemini CLI

12.33%
按下载量换算77

windsurf

8.12%
按下载量换算51

trae

3.25%
按下载量换算20

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。

来源信息

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