Explorar skills
2.905 skills encontradas
nano-banana
This skill should be used for Python scripting and Gemini image generation. Use when users ask to generate images, create AI art, edit images with AI, or run Python scripts with uv. Trigger phrases include "generate an image", "create a picture", "draw", "make an image of", "nano banana", or any image generation request.
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 services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
project-docs
Generate comprehensive, professional project documentation structures including README, ARCHITECTURE, USER_GUIDE, DEVELOPER_GUIDE, and CONTRIBUTING files. Use when the user requests project documentation creation, asks to "document a project", needs standard documentation files, or wants to set up docs for a new repository. Adapts to Python/Go projects and OpenSource/internal contexts.
asdf
Use this skill whenever the user wants to install, configure, or use asdf (asdf-vm), the universal version manager. Trigger for any mention of asdf, .tool-versions files, managing runtime versions, switching between versions of Node.js, Python, Ruby, Go, Terraform, kubectl, Java, Erlang, Elixir, or any other tool managed by asdf. Also trigger when migrating from nvm, pyenv, rbenv, goenv, tfenv, or
code-docs
Apply Google Style documentation standards to Python, Go, and Terraform code. Use when writing or reviewing code that needs docstrings/comments, when asked to "document this code", "add docstrings", "follow Google Style", or when improving code documentation quality. Supports Python docstrings, Go comments, and Terraform variable/output descriptions. Enforces consistent, professional documentation
pydub-automation
Automate repetitive audio tasks with Python using PyDub for batch processing, format conversion, normalization, and content assembly. Use when: Processing large numbers of audio files consistently; Converting between audio formats at scale; Normalizing loudness across a batch of files; Assembling intros/outros automatically to episodes; Trimming silence or extracting segments programmatically
inspecting-skills
Descobre e indexa código Python em skills, permitindo importações entre skills. Use ao importar funções de outras skills ou ao analisar bases de código de skills.
charting
Selecione a biblioteca Python de gráficos adequada (seaborn, matplotlib, graphviz) para produzir visualizações estáticas com qualidade de publicação. Use para criar gráficos, diagramas, mapas de calor e outras visualizações de dados, incluindo diagramas de rede, fluxogramas e diagramas de entidade-relacionamento.
check-tools
Valida instalações de ferramentas de desenvolvimento para Python, Node.js, Java, Go, Rust, C/C++, Git e utilitários de sistema. Use ao verificar ambientes ou solucionar problemas de dependências.
coding-mojo
Desenvolva e execute código Mojo em contêineres do Claude.ai, gerenciando instalação, compilação e execução. Utilize esta skill ao escrever código Mojo, comparar com Python, ou quando mencionar Mojo, Modular ou MAX, encaminhando para skills oficiais da Modular para correções de linguagem.
mocking-test-generator
Generate unit tests with proper mocking for Python (unittest.mock/pytest) or Java (Mockito/JUnit) code. Use when users request test generation, unit tests with mocks, or testing code that has external dependencies like database calls, API requests, file I/O, or network operations. Automatically identifies dependencies to mock and creates executable, maintainable test code.
pseudocode-to-python-code
Convert pseudocode, algorithm descriptions, or specifications into complete, executable Python code. Handles natural language descriptions, structured pseudocode, and formal algorithm specifications. Generates production-ready code with type hints, docstrings, error handling, and test cases. Use when users need to (1) convert pseudocode to Python, (2) implement algorithms from descriptions, (3) tr