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    "title": "Global Stock Exchange Meta Scraper — 25 Exchanges, One Call",
    "description": "One API call for global equities snapshots across 25 stock exchanges. Replaces stitching 25 individual exchange feeds.",
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            "uniqueItems": true,
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                "TWSE",
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                "Taiwan — TWSE",
                "India — NSE",
                "India — BSE",
                "Brazil — B3 (Bovespa)",
                "Hong Kong — HKEX (Hang Seng)",
                "Singapore — SGX",
                "Vietnam — HOSE",
                "Japan — TSE",
                "United Kingdom — LSE",
                "Germany — Xetra / DAX",
                "Canada — TSX",
                "Australia — ASX",
                "Saudi Arabia — Tadawul",
                "Mexico — BMV",
                "South Africa — JSE",
                "Indonesia — IDX",
                "Thailand — SET",
                "Malaysia — Bursa",
                "Turkey — BIST",
                "Philippines — PSE",
                "China — STAR Market",
                "China — ChiNext",
                "China — US-listed ADRs",
                "China — Beijing Stock Exchange",
                "China — Eastmoney A-Shares"
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              "TWSE",
              "NSE_INDIA",
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              "HOSE_VIETNAM",
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              "per_stock"
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            "description": "Shape of the dataset rows. `per_exchange_summary` returns ONE aggregated row per exchange (top 5 gainers, top 5 losers, top 10 by market cap, advancers/decliners, median change) — ideal for daily institutional briefings and hedge-fund snapshots. `per_stock` returns a flat list of normalized stock rows across all selected exchanges (much larger output) — ideal for sector rotation, cross-border ETF construction, and screener workflows.",
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            "title": "Top N stocks per exchange",
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            "maximum": 500,
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            "description": "How many stocks to fetch per exchange. In `per_exchange_summary` mode this controls the underlying universe used to compute aggregates (default 50 is sufficient for top-movers / index leaders). In `per_stock` mode it directly controls dataset size — 100 stocks × 25 exchanges = 2,500 rows. Maximum 500.",
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          },
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            "maximum": 10,
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            "description": "How many sub-actors to run concurrently. Higher = faster wall-clock but more peak memory + risk of provider rate-limits. 5 is the sweet spot for a global snapshot across 25 exchanges (~5 batches of 5).",
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            "title": "Per sub-actor timeout (seconds)",
            "minimum": 60,
            "maximum": 1200,
            "type": "integer",
            "description": "Maximum seconds to wait for any one sub-actor run to complete. If a single exchange screener stalls (regional outage, captcha), it will be cut off and the error recorded in that exchange's row — other exchanges continue. Default 300s (5 min) is plenty for any single screener at topN=500.",
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