# Exception Handling and Recovery

> Catch and react to predictable failure modes (tool errors, rate limits, validation failures) with structured recovery paths.

- **Category**: Agentic AI
- **Subcategory**: Safety & Control
- **Canonical URL**: https://designpattern.fyi/patterns/exception_recovery/

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## Description
**Intent**: Catch and react to predictable failure modes (tool errors, rate limits, validation failures) with structured recovery paths.
**Context**: A team runs a production agent that calls many tools in a loop: search APIs, internal databases, third-party services, model endpoints. In real traffic those tools fail in predictable, repeating ways — the API is briefly down, the caller hit a rate limit, the response came back malformed, the credential was rejected, the request timed out. Each of those failure modes wants a different response from the agent.
**Solution**: Catalogue failure modes. For each, define: detect (typed error), respond (retry / fall back / surface to user / replan), and log. The agent receives a structured error message and can react with a typed branch in its loop.


## Use Cases
- Tool errors, rate limits, or validation failures occur often enough that random retries waste effort.
- Failure modes can be catalogued with typed errors and structured recovery responses.
- The agent loop can branch on typed error messages.





## Trade-offs


### Advantages

- Failure modes become first-class.

- Reliability under partial failures rises.




### Considerations & Drawbacks

- Exception-handling code is its own surface to maintain.

- Hidden retries can mask deeper issues.







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**Reference**: [Original Source](https://www.agentpatternscatalog.org/patterns/exception-handling-and-recovery/)