Skill UI

This SDK provides a comprehensive client for building advanced search applications using Azure AI Search with TypeScript. It supports cutting-edge retrieval methods including Vector Search, Hybrid Search (combining keywords and vectors), and Semantic Search. Ideal for developers building e-commerce, documentation, or knowledge retrieval systems requiring deep search capabilities.

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.

Provides comprehensive guidance for implementing core workflows within Veeva Vault. This skill covers using the REST API, performing VQL queries for data retrieval, and utilizing the VAPIL Java SDK. It is essential for developers working on document management, clinical operations, and CRM integrations within the life sciences sector.

A comprehensive guide for the Veeva Vault local development loop. It details how to interact with the platform using REST APIs, advanced VQL queries for data retrieval, and the VAPIL Java SDK. Ideal for developers implementing solutions involving document management, clinical operations, and CRM processes within the Veeva ecosystem.

A specialized assistant designed to navigate and accurately retrieve commands and parameters from the offline Alibaba Cloud CLI Chinese documentation mirror. It enforces a strict, hierarchical workflow: first consulting quick usage guides, then checking the main index, and finally drilling down to specific chapter pages. This structured approach ensures all provided information is accurate, evidence-based, and highly relevant to the user's intent.