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.
AIDOLS Research Team · Editorial standards
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
Related terms
- AI Agent / Agentic AIAn AI agent is an LLM-driven system that, given a goal, plans a sequence of steps, calls tools or APIs, observes the results, and iterates until the goal is reached — going beyond single-turn chat to multi-step autonomous action.
- Function CallingFunction calling is an LLM capability where the model — given a schema of available functions — emits a structured invocation (function name and JSON arguments) instead of free-form text, letting downstream code execute the call deterministically.
- Semantic SearchSemantic search is information retrieval that ranks documents by meaning rather than exact-keyword overlap, using vector embeddings of query and documents to measure similarity in a learned semantic space.
- Model Context Protocol (MCP)The Model Context Protocol (MCP) is an open standard, introduced by Anthropic in 2024, that lets AI applications connect to external tools, data sources, and services through a common interface — analogous to the Language Server Protocol for editors.
More deployment & operations terms
- Browser-Use AgentA browser-use agent is an AI agent that operates a real web browser to complete tasks — clicking, typing, scrolling, and reading rendered DOM or screenshots — in place of using APIs.
- Code-Interpreter AgentA code-interpreter agent is an AI agent that writes and executes code (typically Python) in a sandbox to answer questions, run analyses, or transform data — using execution as a tool to escape the limitations of pure text reasoning.
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/.