---

name: llama-index description: "Build, customize, troubleshoot, and maintain LlamaIndex Python applications and the LlamaIndex monorepo. Routes ingestion, indexing/querying, agents/workflows, structured outputs, integrations/storage, and repo-maintenance tasks to focused sub-skills." disable-model-invocation: true metadata: disco-role: operating license: MIT

LlamaIndex

Use this repo skill when a task involves LlamaIndex Python (llama-index, llama-index-core, or llama_index.*) application development, integration selection, RAG pipeline construction, agent workflows, structured outputs, or safe monorepo maintenance.

Quick Install Decision

• Use pip install llama-index for the starter package when the user wants the default core + common OpenAI stack.
• Use pip install llama-index-core plus selected integration packages when the user wants a minimal or non-OpenAI install.
• Core imports use llama_index.core.*; integration imports usually use llama_index.<category>.<provider> after installing a matching llama-index-<category>-<provider> distribution.
• Verify a local environment with python scripts/llama_index_core_smoke.py or inspect installed packages with python scripts/inspect_llama_index_install.py --json.

Route By Task

• Data loading and ingestion: use sub-skills/ingestion-and-loading/SKILL.md for SimpleDirectoryReader, Document, node parsers, IngestionPipeline, metadata, cache/docstore, and file parsing failures.
• RAG indexing and querying: use sub-skills/indexing-and-querying/SKILL.md for VectorStoreIndex, retrievers, query engines, response synthesizers, persistence, routing, fusion, and empty retrieval debugging.
• Agents and workflows: use sub-skills/agents-and-workflows/SKILL.md for FunctionAgent, ReActAgent, AgentWorkflow, tools, memory, chat engines, handoff, streaming, and agent orchestration.
• Customization and structured outputs: use sub-skills/customization-and-structured-outputs/SKILL.md for Settings, prompts, callbacks, instrumentation, output parsers, Pydantic schemas, evaluation, and test isolation.
• Integrations and storage: use sub-skills/integrations-and-storage/SKILL.md for provider package selection, import-path mismatches, vector stores, readers, LLM/embedding providers, credentials, and service-backed persistence.
• Repo maintenance: use sub-skills/repo-maintenance/SKILL.md only for work inside the LlamaIndex monorepo: package layout, llama-dev, targeted tests, package metadata, and safe docs/examples automation.

Common Starting Patterns

For a tiny local RAG pipeline:

from llama_index.core import Document, VectorStoreIndex
from llama_index.core.embeddings import MockEmbedding
from llama_index.core.llms import MockLLM
from llama_index.core import Settings

Settings.llm = MockLLM()
Settings.embed_model = MockEmbedding(embed_dim=8)
index = VectorStoreIndex.from_documents([Document(text="LlamaIndex connects data to LLM apps.")])
query_engine = index.as_query_engine()
print(query_engine.query("What does LlamaIndex connect?"))

For real provider-backed usage, set an LLM and embedding model from installed integration packages before creating indexes or agents. If imports fail, route to integrations/storage before changing RAG logic.

Shared References and Scripts

• Read references/package-map.md for package naming, namespace conventions, and how this monorepo splits core from integrations.
• Read references/troubleshooting.md for cross-cutting install/import/provider/API-key/deprecation failures before diving into a narrower sub-skill.
• Read references/repo-provenance.md when deciding whether this skill is stale relative to a LlamaIndex checkout.
• Run scripts/inspect_llama_index_install.py to inspect installed LlamaIndex distributions and import roots without network calls.
• Run scripts/llama_index_core_smoke.py for a tiny core import and mock RAG smoke check.

Boundary Rules

• Do not solve provider import failures by editing core RAG code; first verify the installed llama-index-* distribution and import path.
• Do not assume ServiceContext for new code; prefer Settings and route migration issues to customization.
• Do not run release, publishing, version-bump, credentialed docs sync, or broad integration test commands unless the user explicitly asks and understands the side effects.
• Do not make runtime guidance depend on a source checkout. Copy or adapt reusable checks into this skill’s scripts/ tree and keep source repo examples/tests as evidence only.