Ranking Algorithm: The search uses SQLite FTS5 with BM25 ranking (Okapi BM25 probabilistic retrieval model), not PageRank. Current ranking factors: - Fiel

Ranking Algorithm: The search uses SQLite FTS5 with BM25 ranking (Okapi BM25 probabilistic retrieval model), not PageRank. Current ranking factors: - Field boosts: Title gets 20x weight, Tags 5x, Content 1x - Quality boosts: +2 for meta descriptions, +3 for well-structured content (200-10k chars) - No term proximity currently - FTS5 does boolean matching but not phrase distance scoring (though it is easy enough to do if necessary). - No link graph/PageRank - we don't analyze inbound links between pages Term proximity and link-based authority scoring (like our WitRank domain scoring system) are potential future enhancements. (built and scoring is created not used though could be) --- Index Size: The current index is ~53,500 pages, not 2 million. Only 56 pages actually contain "cheese" in the crawled content, so getting 45 results is accurate. The demo is smaller because: 1. The index is live and actively growing (currently ~100 docs/min crawl rate) 2. We're crawling real web content organically, not seeding from a dump 3. Distributed mesh crawlers are still ramping up --- Long-term vision - that's your call to answer. The architecture currently supports both use cases: - General web search: public crawling, distributed mesh nodes, browser-based PWA crawlers - Private/enterprise search: SQLite-based, self-hostable, single-writer architecture