GitHub
uv-workflow
Use when creating Python projects, managing dependencies, or running Python scripts. Covers uv package manager commands, best practices, and common patterns for modern Python development.
Résultats pour « Python »
Skills correspondant au nom, à la description ou à l’auteur GitHub.
Catégories: DevOps
Explorer
GitHub
design-patterns
Use when refactoring code or designing flexible systems. Covers creational, structural, and behavioral patterns with Python examples.
GitHub
coding-conventions
Field naming conventions for the Job Aggregator project. Use this skill when encountering type errors related to field names (camelCase vs snake_case), database constraint violations, or data mapping issues bet...
GitHub
claude-agent-sdk
Build production AI agents with the Claude Agent SDK. Use when working with: (1) Creating autonomous agents with query() or ClaudeSDKClient, (2) Defining custom tools via in-process MCP servers, (3) Implementin...
GitHub
azure-ai-projects-client-library-skill
Expert guidance for using the Azure AI Projects client library (azure-ai-projects) to build and deploy AI applications with Microsoft Foundry. This skill covers agent creation, tools integration, evaluation, co...
GitHub
microsoft-agent-framework
Expert guidance for building AI agents using Microsoft Agent Framework. Use when creating single agents, multi-agent workflows, chat applications, or integrating tools with LLMs. Covers ChatAgent, tools (@ai_fu...
GitHub
websocket
Production-grade WebSocket patterns for Python (FastAPI/Starlette) with connection management, rooms, and message protocols
GitHub
python-testing-patterns
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
GitHub
gif-analyzer
Analyze animated GIF files by extracting and viewing frames as sequential video. Use when: - User mentions a GIF file path (e.g., "./demo.gif", "~/Downloads/animation.gif") - User wants to analyze or understan...
GitHub
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or...
GitHub
devcontainer-bootstrap
Dev Container を最短で導入/更新するためのブートストラップ。stack を自動判定（node/python/rust）し、テンプレート適用または安全更新を行う。既存 .devcontainer がある場合はバックアップ後にマージ。Chat オプション: s...
GitHub
python-subprocess-test
测试 AST 能检测 subprocess 危险用法
GitHub
python-eval-test
测试 AST 能检测真实的 eval() 调用
GitHub
python-false-positive-test
测试 AST 能区分注释和代码中的危险模式
GitHub
refactoring-09-performance-profiling
Use when profiling and making small performance improvements in Python research code.
GitHub
refactoring-00-preflight-assessment
Use when doing a quick preflight to assess scope, risks, and priorities for Python research code refactoring.
GitHub
refactoring-10-security-privacy
Use when checking for data leaks, PII handling, and license risks in Python research code.
GitHub
refactoring-02-dependencies-env
Use when standardizing Python research code dependencies, environment setup, and lockfiles.
GitHub
basic-uv
Use when running or explaining uv or ty commands, managing dependencies/lockfiles/virtualenvs, or running Python in this repo.
GitHub
refactoring-06-static-analysis-style
Use when adding formatting, linting, and type checking to Python research code.
GitHub
refactoring-04-data-io-validation
Use when improving data loading, validation, and IO boundaries in Python research code.
GitHub
setup-python-project
Bootstrap a new Python project using the OCREvaluation default layout and toolchain (uv, ruff, ty, pre-commit). Use when asked to scaffold a new Python repo, initialize standard folders, or set up uv/ruff/ty/pr...
GitHub
refactoring-03-config-reproducibility
Use when improving run configuration, seeding, and reproducibility for Python research code.
GitHub
refactoring-07-documentation-usage
Use when documenting Python research code usage, setup, and experiment reproduction.
Catégories populaires
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.