memory-consolidate

Memory audit identifies stale opinions and missing topics by cross-referencing stored entries for age, vagueness, and data leaks. It generates a JSON report with findings and suggested actions to resolve gaps between stored memory and current data.

Human-in-the-loop memory consolidation is a process that runs clarification checks with the user to confirm or update memory entries. It keeps stored narratives aligned with reality by resolving detected contradictions and stale opinions through user confirmation.

To refresh project memory at session start, run a Python-based consolidation script that audits user and project memories for missing topics or data leaks. The script outputs a JSON report to guide human-in-the-loop clarifications and keep narratives current.

Yes, memory consolidation requires local memory storage to function. It relies on a Python-based script to access and audit your stored user and project memory entries before generating its JSON report with suggested actions.

You should run a memory audit at the start of each new session, when explicit memory reviews are requested, or whenever contradictions are detected. This ensures your user and project memory entries remain fresh and accurate.