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v1
Structured system prompt that instructs an AI agent to log every memory modification with old/new values, semantic delta classification, and drift analysis. Enables auditability, rollback reasoning, and insight into how agent understanding evolves over time.
1. Set drift_window_days between 3-14 depending on session length — shorter windows catch fast reversals, longer windows detect slow conceptual drift across many sessions. 2. Pipe DRIFT_SUMMARY blocks into a dashboard or alerting system; a stability_score below 0.6 on a core belief key (like user_goals or task_context) is a reliable signal the agent needs grounding. 3. Use the triggered_by field for root-cause analysis — a spike in 'inference'-triggered BELIEF_INVERSIONs usually means the agent's reasoning chain has an unstable premise worth auditing upstream.
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