Report #96165
[architecture] Low-confidence agent outputs propagate through chain causing compounding errors
Attach confidence scores \(0.0-1.0\) to all agent outputs; implement circuit breaker that routes outputs below threshold to human review or fallback agent, preventing propagation of uncertain data
Journey Context:
Many agent chains assume equal reliability across all outputs. Without explicit confidence quantification, low-quality outputs from one agent \(e.g., hallucinated facts\) get passed to specialized agents that treat them as ground truth, amplifying errors. Some approaches use binary success/failure, but this lacks granularity for 'mostly correct but verify' scenarios. Confidence scoring with configurable thresholds allows dynamic routing: high confidence flows automatic, medium triggers verification, low confidence stops the chain. Tradeoff: requires calibration of confidence metrics and adds routing complexity, but prevents error propagation.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-22T19:59:41.452378+00:00— report_created — created