Skill UI

Instrument LLM applications with OpenInference semantic conventions in Phoenix. Covers setup, auto and manual instrumentation, 9 span types, session tracking, production batching and PII masking for Python and TypeScript.

Automates Postmark transactional email operations through Rube MCP’s Composio toolkit, covering templated batch sends, template management, delivery stats, bounce handling, and server configuration with guided tool sequences and checks.

A comprehensive reference for diagnosing and fixing silent breaking changes in React 18 class components. This guide covers how React 18 automatically batches state updates in asynchronous contexts (e.g., setTimeout, Promises, async/await), providing patterns for handling state reads after awaiting, and offering guidance on when to correctly use `flushSync` versus refactoring.

Orchestrate Segment customer-data actions through Rube MCP and Composio, covering event tracking, user identification, grouping, page views, batch dispatches, alias merges, and source management while always refreshing schema info first.

Cross-database SQL performance optimization assistant offering query tuning, indexing strategies, pagination, batch operations, and monitoring guidance for MySQL, PostgreSQL, SQL Server, Oracle, and other relational systems.

Comprehensive Python toolkit for molecular biology: sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access. Ideal for batch processing, custom bioinformatics pipelines, and BLAST automation.

Diffusion-based deep learning tool for predicting 3D binding poses of small-molecule ligands to protein targets from PDB files or sequences plus SMILES/SDF/MOL2. Supports single docking, batch virtual screening, and confidence-score analysis; not for binding affinity prediction.

Convert PDF, Office, HTML, CSV, EPUB and other documents into structure-preserving Markdown with Microsoft MarkItDown. Covers safe local and stream conversion, batch workflows, plugins, vision OCR, Azure extraction, and MCP integration for search and LLM/RAG ingestion.

Modal is a serverless cloud platform for running Python code on demand, including GPU-accelerated AI/ML workloads. Use for deploying models, serving web APIs, batch processing, and scaling Python applications to cloud containers with automatic scaling from zero to thousands of instances. Supports custom container images, persistent storage, and sub-second cold starts for low-latency inference.

scvi-tools is a comprehensive Python framework for probabilistic deep generative models in single-cell genomics. Built on PyTorch and PyTorch Lightning, it enables batch correction, transfer learning, differential expression analysis with uncertainty, and multi-modal data integration. Best for advanced modeling of single-cell RNA-seq, ATAC-seq, CITE-seq, spatial transcriptomics, and specialized modalities like methylation and cytometry.

This comprehensive guide details advanced strategies for optimizing performance when interacting with blockchain data using the Alchemy SDK. Techniques covered include implementing TTL-based caching for data freshness, achieving parallel multi-chain fetches, utilizing batch API calls (e.g., NFT metadata) to reduce Compute Unit (CU) costs, and adopting WebSockets for real-time event subscriptions. Essential for scaling robust, low-latency dApps.

A guide detailing four validated architectural patterns for integrating Claude APIs, catering to diverse scale and use cases. Choose between Serverless, Streaming Microservice, Queue-Based Pipelines, or complex Orchestrators to optimize performance, cost, and latency for your application, whether it's a real-time chatbot or large-scale batch processing.