AI agent tool-call latency includes request construction, scheduling, network transit, authentication, service execution, response transfer, parsing, and any retries. An agent may make many sequential calls, so moderate delay per tool can dominate total task time.
Latency can be reduced with parallel independent calls, local execution, caching, fewer round trips, streaming, suitable timeouts, and faster services. Optimization must preserve correctness, permissions, rate limits, and clear handling of partial or timed-out results.
ELI5
Agent tool-call latency is the waiting time added when an AI agent asks a tool or service to do something and processes the reply. A small delay can become a large part of the total task time when many calls happen one after another.
For example, if five independent information requests each take two seconds and run sequentially, the agent may wait about ten seconds. Running safe independent calls together can reduce that delay, but the agent still needs correct timeouts and careful handling of missing or partial results.
