v0.6.2 — shortlist retrieval, self-healing embeddings, sharper memory

• Memory retrieval shortlists instead of reading the whole store. Above memory.full_scan_threshold (default 500 active memories) each search scores a provably-complete candidate shortlist; smaller stores keep byte-identical full-scan behavior, a shortlist that cannot narrow retreats to the full scan with a loud warning, and results, gates, weights, and ranking are unchanged.
• Active memories missing an embedding vector heal themselves at startup via a model-scoped, bounded, non-blocking backfill, so enabling embeddings or changing models never leaves part of the store invisible to semantic search.
• The offline corpus runner gained a --candidates flag so the evaluation gate exercises both retrieval modes.
• A retrieval pass that reads its 5,000-row ceiling now logs a warning instead of truncating silently.
• Extraction is more selective about procedures: generic how-to answers are no longer memorized; a procedure is remembered only when it describes the user's own project, environment, or decisions.