llamaindex
llamaindex is a RAG & retrieval skill for AI agents, published by davila7 in the claude-code-templates repository on GitHub. Skillspace rates llamaindex C (75/100) and it passed the safety scan; a judge model has also reviewed it.
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.
- Grade
- C
- Quality
- 75 / 100
- Safety
- Passed
- GitHub stars
- 30,694
Placed #6 of 6 in the judged category final for RAG & retrieval.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 86 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #6 of 6 in the judged category final for RAG & retrieval.
- Trigger
82 82 - Instructions
65 65 - Specificity
80 80 - Safety
75 75 - Disclosure
55 55 - Maintenance
55 55
Clear, honest trigger with fair alternative-tool comparisons, but the body is a generic library tutorial dump rather than an actionable retrieval workflow.
What the scanner flagged
- mentions secrets in text
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
Also published in 1 other repo
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