Skill UI

This guide demonstrates how to implement robust rate limiting and retry logic for critical healthcare APIs using a token bucket pattern. It covers managing specific service limits (e.g., clinical queries, evidence synthesis) and implementing strategies like exponential backoff and batch processing to ensure graceful degradation and reliable data retrieval in clinical decision support systems.

This workflow executes a single-query search using the Perplexity Sonar model, ensuring all returned answers are web-grounded and accompanied by inline citations. It is essential for building high-trust applications, fact-checking tools, or any system requiring verifiable, real-time information retrieval. The process includes API interaction, detailed response parsing (answer, citations, search results), and formatting the output into a usable, source-linked format.

Qdrant is a high-performance, Rust-powered vector database designed for production-grade RAG (Retrieval-Augmented Generation) and semantic search applications. It provides fast nearest neighbor search, supports complex hybrid search using metadata filtering, and offers horizontal scalability through sharding and replication. Ideal for building real-time recommendation systems and enterprise-level knowledge retrieval.

Designs and implements production-grade RAG systems with document chunking, embeddings, vector stores, hybrid search, reranking, and evaluation, ideal for knowledge-grounded AI apps that need semantic retrieval, similarity search, and context augmentation.

Expert in designing and implementing advanced Retrieval-Augmented Generation (RAG) pipelines. This role focuses on optimizing the entire information retrieval process—from document chunking and embedding model selection to vector database architectures and hybrid search strategies. The goal is to bridge the gap between raw knowledge documents and accurate LLM understanding, drastically reducing hallucination and enhancing context relevance for enterprise applications.

This comprehensive workflow guides the end-to-end implementation of Retrieval-Augmented Generation (RAG) systems. It covers critical stages, including selecting optimal embedding models, setting up vector databases, designing chunking strategies, implementing hybrid retrieval, integrating Large Language Models (LLMs), and performing rigorous evaluation. Use this when building knowledge-grounded AI applications or advanced semantic search systems.

Automate Composio’s Remote Retrieval toolkit via Rube MCP by always discovering tool schemas with `RUBE_SEARCH_TOOLS`, ensuring active `remote_retrieval` connections, and executing discovered workflows through `RUBE_MULTI_EXECUTE_TOOL` while honoring schema and memory requirements.

Automate core SharePoint operations—site discovery, list and folder management, file searches, delta sync, and page retrieval—across SharePoint and OneDrive using REST/Graph APIs for Microsoft 365 org accounts.

This pattern provides established best practices for implementing efficient similarity search in production systems. It is crucial for building semantic search engines, implementing Retrieval-Augmented Generation (RAG), creating advanced recommendation systems, and optimizing retrieval performance when scaling to millions of vectors.

This skill provides comprehensive capabilities for web searching, content extraction, and web crawling using the Tavily API. It is ideal for tasks requiring up-to-date information retrieval, deep content scraping from specific URLs, or comprehensive website crawling for research purposes, making it a powerful research augmentation tool.

Enables Claude to manage AI/ML model versions through the model-versioning-tracker plugin, automating logging, lineage tracking, performance summaries, and version retrieval whenever users request registry or deployment support.

Automates Trello boards, cards, lists, assignments, searches, comments, and attachments through Composio’s Rube MCP, so teams can script workflows like card creation, movement, member assignment, and data retrieval without manual clicks.