llamaindex
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.
Install
npx skills add davila7/claude-code-templates@llamaindexRuns in your terminal. Adds the skill globally for Claude Code, Cursor, Codex and others; add -g -y to skip prompts.
What it does
LlamaIndex - Data Framework for LLM Applications The leading framework for connecting LLMs with your data. When to use LlamaIndex Use LlamaIndex when: - Building RAG (retrieval-augmented generation) applications - Need document question-answering over private data - Ingesting data from multiple sources (300+ connectors) - Creating knowledge bases for LLMs - Building chatbots with enterprise data - Need structured data extraction from documents Metrics: - 45,100+ GitHub stars - 23,000+ repositories use LlamaIndex - 300+ data connectors (LlamaHub) - 1,715+ contributors - v0.14.7 (stable) Use…
Excerpt from the skill's own SKILL.md. Read the full file on GitHub before installing: skills run with your agent's permissions.
View source on GitHubBefore you install
Skills are plain text instructions the agent follows, sometimes with scripts. Check the source, prefer repositories with many installs and stars, and read any script it ships.
Categories
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