Tool Error Handling
What an agent does when a tool call fails — and whether it recovers gracefully or falls apart.
Think of it like
A cook whose oven dies mid-service — do they adapt and finish, or stand there staring at it?
Example
The database tool times out, so the agent reads the error, waits a moment, and retries once before trying a different approach.
How it actually works
Tools fail constantly — timeouts, bad inputs, rate limits — and how the error is surfaced to the model decides whether it recovers. A clear, structured error (“missing required field: date”) lets the agent fix and retry; a raw stack trace or silent failure sends it into confusion or a loop. Robust agents treat errors as information to act on, not dead ends, which means the error messages themselves become part of the design.
For product teams
Real tools fail often; how the agent handles those failures is most of what separates a demo from production.
For engineers
Surface tool failures as structured, actionable observations so the model can correct rather than loop or stall.
Related
- Retry Logic — A common recovery strategy.
- Fallback Tool — Switching to a backup when a tool keeps failing.
- Looping — What a stuck agent does instead of recovering.
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