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Deployment & Operations

Tool Router

A tool router is a layer in an agent system that selects which tool (or subset of tools) to expose to the model for a given query, instead of putting all tool definitions in every prompt.

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Full definition

Models degrade as the tool count grows past 20–50 — accuracy of tool selection drops, and prompt cost rises. Tool routers solve this by retrieving a small candidate set (semantic search over tool descriptions, hierarchical category routing, or a fine-tuned classifier) and showing the model only those tools. Modern stacks: tool search with deferred tool loading (OpenAI's Responses API for gpt-5.4 and later; Anthropic's Tool Search Tool), MCP servers that expose only a subset of tools, and tool retrieval in LangGraph (langgraph-bigtool).

Why it matters

Any enterprise agent with >30 tools needs a tool router to stay accurate and affordable. Without one, prompt cost grows linearly with tool count and selection accuracy collapses — a common reason agent pilots fail to scale.

Example

An IT-helpdesk agent has 240 tools across systems; a tool router (BGE embedding over tool docstrings) returns the top-8 candidates per query, raising tool-selection accuracy from 51% to 89% and cutting prompt tokens 70%.

Next steps

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Source & further reading

Primary source: OpenAI — "Tool search" (official guide) (2026).

Citation policy: this entry is part of the AIDOLS AI Implementation Glossary and may be quoted for research, journalism, and education with attribution to aidolsgroup.com/en/glossary/tool-router/.