mnemo — a zero-dependency memory layer for AI agents

• Value-ranked recall — top-k by relevance × accrued value, not cosine alone.
• Per-type decay + capacity-aware consolidation — the "dream" pass links near-duplicates and marks stale/superseded, never rewriting the raw note.
• Lexical + semantic auto-mode — BM25 + embeddings fused by Reciprocal Rank Fusion.
• Contradiction flagging — mutually-incompatible memories surface for review, never auto-deleted.
• Corroboration-gated influence (0.4.0) — recall(influence_only=True) restricts the memories allowed to drive an action to those that earned corroboration (a credited good outcome, or ≥2 distinct-source links).

Why 0.4.0 matters: poison-resistant recall

• A plain-English trigger sentence in one poisoned memory hijacks raw top-1 retrieval 88–100%, is scale-invariant (60→10 000 memories), and evades a perplexity filter.
• Retrieval-time / embedding-geometry defenses do not generalize across encoders.
• recall(influence_only=True) drops the single-instance poison's rank-1 hijack to 0% on MiniLM / BGE / Contriever and every scale — because it lives in provenance metadata, not embedding geometry. Honest cost: a rare-but-true memory that hasn't earned corroboration is filtered too (recall 1.00 corroborated vs 0.08 uncorroborated), so this mode is for adversarial / untrusted ingestion. It raises attacker cost (≥3 coordinated records + ≥2 forged independent provenances), it does not make poisoning impossible.