Individual skill
agents-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.
cli-tool/components/skills/ai-research/agents-llamaindex/SKILL.md
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- anthropic Repository topic
- anthropic-claude Repository topic
- claude Repository topic
- claude-code Repository topic
- agent-skills Repository topic
- ai-agents Repository topic
- claude-code-plugins Repository topic
- cli Repository topic
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- agents Declared skill tag
- llamaindex Declared skill tag
- rag Declared skill tag
- document-ingestion Declared skill tag
- vector-indices Declared skill tag
- query-engines Declared skill tag
- knowledge-retrieval Declared skill tag
- data-framework Declared skill tag
- multimodal Declared skill tag
- private-data Declared skill tag
- connectors Declared skill tag
- data Derived category
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Read excerpt
# 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
