llamaindex
Build LLM applications with LlamaIndex. Create indexes, query engines, and data connectors. Use for RAG applications, document search, and knowledge base systems.
npx skills add majiayu000/claude-skill-registry --skill llamaindex-fgarofalo56-suppercharge-microso --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LlamaIndex Skill Complete guide for LlamaIndex - data framework for LLM applications. ## Quick Reference ### Core Components | Component | Description | |-----------|-------------| | **Documents** | Data containers | | **Nodes** | Document chunks | | **Indices** | Searchable structures | | **Query Engines** | Question answering | | **Agents** | Autonomous reasoning | | **Tools** | Agent capabilities | --- ## 1. Installation ```bash # Core pip install llama-index # With all integrations pip install llama-index[all] # Specific integrations pip install llama-index-llms-openai pip install llama-index-embeddings-openai pip install llama-index-vector-stores-chroma pip install llama-index-readers-file ``` --- ## 2. Basic Setup ### Initialize ```python from llama_index.core import Settings from llama_index.llms.openai import OpenAI from llama_index.embeddings.openai import OpenAIEmbedding # Configure defaults Settings.llm = OpenAI(model="gpt-4o", temperature=0.1) Settings.embed_model = OpenAIEmbedding(model="text-embedding-3-small") Settings.chunk_size = 1024 Settings.chunk_overlap = 200 ``` ### Quick Start ```python from llama_index.core import VectorStoreIndex, SimpleDirectoryReader #
- Quick Reference
- Core Components
- 1. Installation
- 2. Basic Setup
- Initialize
- Quick Start
- 3. Document Loading
- File Readers
- Specialized Readers
- Create Documents Manually
- 4. Indices
- Vector Store Index
- With External Vector Store
- Summary Index
Core pip install llama-index With all integrations pip install llama-index[all] Specific integrations pip install llama-index-llms-openai pip install llama-index-embeddings-openai pip install llama-index-vector-stores-chroma pip install llama-index-readers-file
What does the llamaindex skill do?
Build LLM applications with LlamaIndex. Create indexes, query engines, and data connectors. Use for RAG applications, document search, and knowledge base systems.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill llamaindex-fgarofalo56-suppercharge-microso --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.