memory-hygiene

# memory-hygiene — Stale Memory Detection and Re-Verification > Addresses the "stale-but-confident" failure mode: verified information that silently drifts > while remaining highly ranked in retrieval — identified as a harness failure mode > in *Scaling the Harness in Agentic AI* (arXiv:2605.26112). > > **Sister asset**: arXiv:2607.01935 (*A-TMA: Decoupling State-Aware Memory Failures in Long-Term > Agent Memory*, Shi/Tang/Tung 2026) names this exact class "ghost memory" — outdated / current / > transitional facts intermixing during retrieval — and benchmarks it (LTP; conflict-accuracy +0.240, > temporal-F1 0.03→0.17 on LoCoMo with a bank-maintenance layer). It is the tighter external frame for > what memory-hygiene detects: this skill is the FH-native *detection + archival* pass over the same > failure A-TMA formalizes at the retrieval layer. (Source-verified 2026-07-03; a broader bounded-memory > testbed, arXiv:2607.02255 AgenticSTS, was considered and set aside — it targets context-assembly, not > staleness, so it is not the sister here.) FH is an online-first harness. Its memory entries point to live external resources (GitHub repos, arXiv records, Zenodo DOIs, monitoring routines). These drift faster than in offline systems — which makes hygiene both more necessary and more tractable (live re-verification is possible). ## Trigger Conditions ### Natural Language Triggers | Phrase | Intent | |---|---| | "memory check", "check stale memories" | Manual hygiene scan | | ...