Agent Error Recovery

What it does

The agent-error-recovery skill allows AI agents to gracefully handle and recover from errors encountered during task execution. It provides mechanisms for identifying error types, attempting alternative approaches, and logging detailed information about failures. This ensures the agent can continue operating effectively even when unexpected issues arise.

When to use it

• Complex workflows: When an agent is performing a series of steps with dependencies, this skill helps prevent complete failure due to individual errors.
• Unreliable APIs: If an agent interacts with external services that are prone to downtime or intermittent failures, error recovery can maintain progress.
• Data processing pipelines: When agents process data from various sources, the skill ensures resilience against corrupted or unavailable datasets.
• Long-running tasks: For tasks that take a significant amount of time, this skill minimizes wasted effort by automatically retrying failed operations.

Key capabilities

• Error type identification
• Retry mechanisms with configurable delays
• Alternative approach selection
• Detailed error logging and reporting

Example prompts

• "Agent, if you encounter an error while scraping the website, try a different user agent."
• “When retrieving data from the API, implement retry logic with exponential backoff.”
• "If the file upload fails, log the error details to the console and attempt a different storage location."

Tips & gotchas

The skill requires careful configuration of retry parameters (delay, number of attempts) to avoid overwhelming external services. Ensure your agent has sufficient context or knowledge to select appropriate alternative approaches when errors occur.