rag-implementation
rag-implementation is a RAG & retrieval skill for AI agents, published by Dokhacgiakhoa in the Agent-skills-setup-for-AntiGravity repository on GitHub. Skillspace rates rag-implementation C (73/100) and it passed the safety scan; the rating is based on static analysis only.
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.
- Grade
- C
- Quality
- 73 / 100
- Safety
- Passed
- GitHub stars
- 503
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
- 94 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 5 other repositories, in 6 collections
- Scope
- Portable: works in any project. General RAG architecture guidance, product-agnostic
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
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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