Lesson 2094 of 2116
AI Agent Tool Design: APIs Built for LLM Consumers
Tool API design for AI agents differs from API design for humans — here's how.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2tool schema
- 3error semantics
- 4atomicity
Concept cluster
Terms to connect while reading
Section 1
The premise
Tools designed for AI agent consumption favor verbose names, structured errors, and atomic operations over the terse, fluent APIs humans prefer.
What AI does well here
- Calling well-named tools with descriptive parameters correctly
- Recovering from errors that include suggested next actions
- Composing atomic tools into multi-step workflows
- Preferring tools whose names and descriptions match intent
What AI cannot do
- Recover gracefully from opaque error codes without context
- Choose between near-duplicate tools with subtle differences
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