Definition
An agent routing layer is the component (often custom code or a framework primitive like LangGraph) that sits between the LLM's intent and the available tools, deciding which tool to call based on the intent and the tools' affordances (descriptions, names, prior success rates).
In Depth
Without a dedicated routing layer, agents rely on the LLM's tool-selection from raw tool descriptions. This works at 3-5 tools and degrades quickly past 8-10. Routing layers help by: (1) filtering the tool list per intent (the LLM only sees relevant tools); (2) keeping prior-call state (if last call was reddit_search, weight the next call differently); (3) injecting explicit routing rules ('for trading queries, always start with the news_search tool'). The r/LangChain post that called LangChain agents 'amnesic' specifically built a routing layer; the metric jumped from 48% to 94% task success. The complementary fix on Scavio's side: tools are named semantically (search, reddit_search, youtube_search, amazon_search, walmart_search, extract) so the routing decisions are less ambiguous by construction.
Example Usage
An LLM with 12 attached tools and no routing layer scored 48% on a 5-step research benchmark. After adding a routing layer that filters tools to 4 per intent and tracks last-tool-called, the same LLM scored 94% on the same benchmark.
Platforms
Agent Routing Layer is relevant across the following platforms, all accessible through Scavio's unified API:
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