Retain-time atomic fact extraction — the keystone that gives reflect something structured to aggregate over.

Faithful port of Hindsight's engine/retain/fact_extraction.py: each incoming retain item (a chat session, document, or paragraph) is decomposed by an LLM into a LIST of atomic facts, one input to N discrete memory units. Whole-session blobs cannot be aggregated across sessions (the buried "took course X" / "spent €40" facts never individuate, so cross-session counts and temporal ordering are unanswerable); atomizing them restores the material that recall ranks, consolidation merges into observations, and reflect sums.

Each produced fact-item INHERITS the parent's provenance and — critically — its mentioned_at (the session date), so every atomic fact carries the timestamp reflect's per-entry temporal arithmetic depends on. Extraction OVERRIDES only content (the assembled fact text), type (world/experience), and the occurred_* dates for datable events.

Extraction is gated: it runs only when a mode is configured AND an extraction-capable LLM is available. It degrades to passthrough (the original item, i.e. today's blob behaviour) on any LLM error, timeout, or empty result — extraction never fails a retain. This mirrors the LlmCore isolation the rest of the pipeline relies on.