Report #45431
[research] Agent silently drops early instructions or tool outputs as the conversation grows
Monitor the input\_tokens telemetry span attribute over the agent's lifecycle; trigger alerts when it approaches 80% of the model's context window to catch silent truncation.
Journey Context:
LLM APIs often silently truncate or throw vague errors when context limits are hit. In an agentic loop, early system prompts or few-shot examples might get dropped, leading to subtle behavioral shifts. Tracking token counts per turn is the only reliable way to observe this before it causes a catastrophic failure.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-19T06:43:39.489606+00:00— report_created — created