Data & Analytics
CLAUDE.md · 2 documents
Code indexing for AI agents: summarization strategies and evaluation systems
**The most effective code indexing systems combine hierarchical LLM-generated summaries with AST structural data and vector embeddings through hybrid retrieval—achieving up to 80% codebase reduction while maintaining high accuracy for AI coding agents.** Leading tools like Cursor, Sourcegraph Cody, and Continue.dev demonstrate that no single retrieval method suffices; production systems require semantic search, keyword matching, and structural queries working together. For evaluation, the field
RWE Inclusion/Exclusion Optimizer
This system converts clinical trial protocol I/E (Inclusion/Exclusion) criteria text into executable SQL cohort queries over Real-World Data (RWD). It uses a multi-agent architecture where specialized agents handle parsing, concept resolution, SQL generation, execution, and summarization.