Reduce Agent Errors and Token Costs with Semantic Tool Selection

When AI agents have many similar tools, they often select the wrong one and consume excessive tokens by processing all tool descriptions. Semantic tool selection filters tools before the agent processes them, which improves accuracy and reduce token costs. We'll build a travel agent with Strands Agents and use FAISS to filter 29 tools down to the top 3 most relevant, comparing filtered vs unfiltered results. In Part 1 , Graph-RAG prevented agents from hallucinating statistics. But agents still hallucinate during tool selection choosing the wrong tool even with correct data. This Series: 4 Production Techniques Part 1 : GraphRAG - Relationship-aware knowledge graphs preventing hallucinations in aggregations and precise queries Part 2 (This Post): Semantic Tool Selection - Vector-based tool filtering for accurate tool selection Part 3: Neurosymbolic Guardrails - Symbolic reasoning for verifiable decisions Part 4: Multi-Agent Validation - Agent teams detecting hallucinations before damage