How to Audit Agent Trajectories for Memory Failures

A trajectory audit traces an agent’s retrievals, decisions, and tool calls to identify the first observable failure, even when a plausible final answer conceals missing or mishandled evidence. It should distinguish observed failures from possible explanations, define clear run-level and step-level denominators, and capture a structured evidence chain including source identifiers, retrieved and selected context, authorization scope, system readiness, configuration versions, and separate tool intentions from actual external outcomes. Consistent failure labels such as absent or unready sources, incorrect scope or version, poor ranking, dropped context, misinterpretation, and failed tool actions help make reviews comparable, while ambiguous cases should remain unresolved until evidence supports a classification. Audits should use positive and negative examples for labels, permit transparent reclassification, and test fixes through stable redacted replay fixtures that include unaffected cases to detect tradeoffs such as increased irrelevance or latency. The approach emphasizes starting with a small number of inspectable runs, integrating recurring findings into logs and alerts, using debugging guides and applicable benchmarks such as MemoryBench, and retaining application-specific traces for reliable evaluation.

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