AI & Machine Learning
Prune Agent Memory
Audit, classify, and selectively forget stored memories. Covers memory enumeration and classification by type/age/access frequency, staleness detection for outdated references, fidelity checks using external anchors, a decision tree for selective withdrawal, tombstoned deaccession so removed content stays recoverable, counter-memory inoculation for failed strategies that would otherwise be re-derived, preemptive filtering rules for what should never become memories, and an audit trail so forgetting itself is reviewable. Use when memory has grown large and uncurated, when project state has shifted significantly since memories were written, when retrieval quality has degraded, or as periodic maintenance alongside manage-memory.
- Publisher / source
- pjt222/agent-almanac (found on the CSV list)
- Upstream record
- pjt222/agent-almanac
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
8e7fb971dd1860a78de8971b107d6623e0bc32c833c350d55f0151a91d27409f