Retrieve relevant information through RAG
Retrieve relevant information through RAG is a RAG & retrieval skill for AI agents, published by run-llama in the vibe-llama repository on GitHub. Skillspace rates Retrieve relevant information through RAG D (59/100) and it passed the safety scan; the rating is based on static analysis only.
Leverage Retrieval Augmented Generation to retrieve relevant information from a a LlamaCloud Index. Requires the llama_cloud_services package and LLAMA_CLOUD_API_KEY as an environment variable.
- Grade
- D
- Quality
- 59 / 100
- Safety
- Passed
- GitHub stars
- 177
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 91 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 1 other repositories, in 2 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- 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
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