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v1
Systematically log, diff, and analyze every change to an AI agent's memory store. Identifies substantive knowledge shifts vs. cosmetic edits, surfaces drift patterns, and generates audit reports for debugging, compliance, and learning analysis.
1. Pipe memory snapshots directly from your agent's state serializer — JSON, YAML, and plain key-value formats all work well as inputs. 2. Run this prompt after every significant agent interaction and store outputs in a time-series log (e.g., append to a JSONL file) to build a full evolution history you can query later. 3. For conflict detection to be most useful, ensure your memory system uses stable key names — frequently renamed keys will generate false CONFLICT classifications.
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