ol_filing_search
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) -- set OXFORD_LEDGE_USER_ID + OXFORD_LEDGE_USER_TIER in your client config or the 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.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| k | No | Number of chunks to return (default 5, hard cap 15). | |
| query | Yes | Natural-language question to retrieve relevant filing passages for. | |
| ticker | Yes | Stock ticker symbol (e.g. AAPL) |