v0.6.0 — Periodic deep consolidation

• Periodic deep consolidation ships as an opt-in third memory-maintenance timescale: a background sweep detects duplicated memories within large topics and merges them, off by default and gated on learning being enabled with a configured learning model.
• Each consolidation pass clusters a bounded working set deterministically and makes a single bounded model proposal; deterministic code owns every mutation, applied only through the same guarded reinforce/supersede primitives the per-turn learner already trusts.
• A per-topic checkpoint is stamped after mutations, so consolidation's own writes never count as churn for the next window; oversized topics advance through explicit continuation passes that bypass only the churn floor.
• Every pass records a consolidation.pass audit event; contradictions surface as inert consolidation.conflict events that nothing auto-resolves, and affected topic summaries rebuild through the existing dirty-marking path.
• Consolidation is implemented at topic-level depth; cross-topic and corpus-wide passes remain deferred.