error-recovery

Handle external model timeouts in multi-agent workflows by implementing retry or skip options. This skill manages delays exceeding 30 seconds, allowing the process to proceed with available results instead of derailing entirely.

Recover from API rate limiting and 5xx errors in AI pipelines by applying exponential backoff strategies. This approach automatically manages retry intervals to ensure workflow resilience and production readiness during transient network failures.

Graceful degradation when API credits are exhausted works by falling back to embedded models. This ensures the workflow continues processing with available local resources rather than failing due to missing external dependencies.

Yes, you can save partial workflow results if a user cancels a multi-agent process. The mechanism gracefully handles user cancellations like Ctrl+C, logging progress and preserving successful outputs before exiting.

Continue multi-agent workflows when API calls fail with 401 errors by proceeding with partial success. The workflow skips the failed agents and continues using the successful results, informing the user about the failures.