Why LLM Agents Fail Silently and How to Debug Them

Short summary

LLM agents often fail silently—returning empty results without exceptions when they hit token limits, tool schemas drift, or exceptions get swallowed. Debug this by instrumenting agent loops with OpenTelemetry spans to track finish reasons and token usage, validating tool outputs with Pydantic before downstream use, and explicitly reraising exceptions instead of catching them silently. Integrate with tracing backends like Honeycomb or Jaeger for real-time visibility into multi-step agent chains.

• •Silent failures occur when agents complete without exceptions but produce wrong/incomplete results
• •Debug with OpenTelemetry spans per step to track finish reasons, tokens, and tool calls
• •Validate tool outputs with Pydantic and explicitly reraise exceptions to catch contamination early

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