ol_filing_search

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MOAT (PAID -- AI): semantic retrieval over EMBEDDED SEC filings for a ticker. Ask a natural-language question ('what did they say about supply-chain risk?') and get the most relevant filing CHUNKS back from an Oxford Ledge hybrid retrieval (lexical BM25 plus a dense pass, fused by reciprocal rank). This is the ONE metered tool: it draws on your daily AI quota (25 searches/day, UTC reset, plus a burst limiter) -- it needs a signed-in account or an API key, and an anonymous call fails AUTH_REQUIRED. Returns {summary, ticker, count, chunks, quota_remaining_today}; each chunk is {section, text (an excerpt), accession, url, score}. `score` is the FUSED RANK score (4dp), NOT a similarity: compare it only within one response. `k` default 5, hard cap 15. Source: SEC EDGAR filings (Oxford Ledge embedded corpus). Caveats ride the response's tool_notes. Needs an Oxford Ledge API key that the client's operator configures; anonymous callers are refused.