Individual skill
agentsop-llamaindex
Operating-system distillation of LlamaIndex — the leading RAG / document-agent framework. Activate when the calling agent must build, debug, harden, or evaluate a Retrieval-Augmented Generation pipeline over unstructured/private data, decide between RAG primitives (Index types, retrievers, query engines, routers, agents), or pick LlamaIndex vs LangChain / Haystack / raw vector store for a coding task. Encodes the 5-layer mental model (Documents → Nodes → Indices → Retrievers → Query Engines / Response Synthesizers), the canonical RAG bootstrap SOP from baseline `VectorStoreIndex` through hybrid + reranker + eval-loop hardening, the official 13-failure-mode checklist, and 5 dilemma cases distilled from docs, GitHub issues, and 2025 production post-mortems.
skills/agentsop-llamaindex/SKILL.md
Source commit cf4376869e5f23f82404c3021a2a1315dfca318d
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- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Instructions only
- Last checked
- Nov 6, 2026
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Repository context
- Repository stars (not skill ratings)
- 463
- Repository last updated
- Oct 24, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skill Repository topic
- skill-creation Repository topic
- ai-agent Repository topic
- llm-agent Repository topic
- skill-engineering Repository topic
- skill-generation Repository topic
- skill-pipeline Repository topic
- skill-construction Repository topic
- agent-skills Repository topic
- skill-acquisition Repository topic
- engineering Derived category
- data Derived category
- docs Derived category
Files and excerpt
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Browse files
README.mddoc · 1,122 bytesSKILL.mdcore · 26,201 bytesSKILL.mdcore · 26,201 bytesSKILL.mdcore · 26,201 bytesintermediate/operation_candidates.jsonasset · 7,218 bytesreferences/R1-architecture.mddoc · 8,900 bytesreferences/R2-sop-workflow.mddoc · 9,156 bytesreferences/R3-dilemma-cases.mddoc · 14,592 bytesreferences/R4-anti-patterns.mddoc · 10,170 bytesreferences/R5-ecosystem-context.mddoc · 8,387 bytes
Read excerpt
# LlamaIndex · SOP
> Third-person analytical view of how LlamaIndex *thinks* about turning private
> documents into a grounded answering system. The skill is for an LLM agent that
> writes / reviews / debugs RAG code — not for an end user reading docs.
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## 何时激活 (Activation Rules)
Activate this skill when any of the following holds:
1. The user's request involves building, modifying, or debugging a **RAG pipeline** (retrieval over private/unstructured data + LLM synthesis).
2. The user mentions **LlamaIndex** (`from llama_index...`), **LlamaParse**, **LlamaCloud**, or a LlamaIndex-style primitive (`VectorStoreIndex`, `SummaryIndex`, `IngestionPipeline`, `QueryEngine`, `SubQuestionQueryEngine`, `RouterQueryEngine`, `Settings`, `Workflows`).