Explorar skills
2.905 skills encontradas
azure-storage-file-share-py
Azure Storage File Share SDK for Python. Use for SMB file shares, directories, and file operations in the cloud.
copilot-sdk
Build applications that programmatically interact with GitHub Copilot. The SDK wraps the Copilot CLI via JSON-RPC, providing session management, custom tools, hooks, MCP server integration, and streaming across Node.js, Python, Go, and .NET.
azure-servicebus-py
Azure Service Bus SDK for Python messaging. Use for queues, topics, subscriptions, and enterprise messaging patterns.
azure-monitor-opentelemetry-exporter-py
Azure Monitor OpenTelemetry Exporter for Python. Use for low-level OpenTelemetry export to Application Insights.
scikit-learn
Machine learning in Python with scikit-learn. Use for classification, regression, clustering, model evaluation, and ML pipelines.
pdf-official
This guide covers essential PDF processing operations using Python libraries and command-line tools. For advanced features, JavaScript libraries, and detailed examples, see reference.md. If you need to fill out a PDF form, read forms.md and follow its instructions.
networkx
NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.
azure-cosmos-py
SDK do Azure Cosmos DB para Python (API NoSQL) para operações CRUD de documentos, consultas, contêineres e dados distribuídos globalmente.
mcp-tool-developer
Build Model Context Protocol (MCP) servers and tools from scratch. Full-stack MCP development with TypeScript/Python, testing, deployment, and registry publishing.
temporal-python-testing
Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.
pubmed-database
Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.
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.