rag-implementation
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.
71
2.12x
Quality
66%
Does it follow best practices?
Impact
70%
2.12xAverage score across 3 eval scenarios
Securityby
Passed
No known issues
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npx tessl skill review --optimize ./tests/ext_conformance/artifacts/agents-wshobson/llm-application-dev/skills/rag-implementation/SKILL.mdNo security issues found
Scanned
- Repository
- Dicklesworthstone/pi_agent_rust
- Commit
47823e3
- Audited
- Security analysis
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