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OneSource Deepstate Depth History
x402
OneSource Deepstate Depth History is a paid API for AI agents from api.onesource.io, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-14).
Returns a time-series heatmap of resting order sizes by price level for a given order book market, with configurable time range and resolution
Price / call$0.02
Success—
StatusUnknown
How this service works
Deepstate, the on-chain order-book exchange on Robinhood Chain. Depth heatmap - resting order size by price level over time for a market.
Output
Returns a time-indexed array of depth data points, each containing the price bucket, side (bid/ask), resting order size (raw and denominated), order count, block number, market session, and finality status. Also includes book metadata (ID, slug, label), the queried time range, resolution, and coverage statistics (total order and denominated order counts). Size token metadata (symbol, address, decimals) is included for unit interpretation.
Example use cases
Liquidity concentration analysis for trading strategy
“Pull the daily ask-side depth history for the BTC-USDC book on Deepstate for the past 30 days — I want to see which price levels had the most resting sell orders so I can identify resistance zones.”
Market microstructure research heatmap
“Get me hourly order book depth snapshots for both bids on the ETH-USDC Deepstate market from 2024-10-01 to 2024-10-31 so I can build a heatmap of where liquidity was concentrated over the month.”
Real-time order book depth monitoring for alerts
“Fetch the latest 1-hour resolution depth history for the SOL-USDC book on Deepstate through today — I need the resting order sizes at each price level to check if there's been any big change in bid-side liquidity in the last 24 hours.”
Technical details
Endpoint
GEThttps://api.onesource.io/deepstate/v1/analytics/depth-historyWhen to prefer
Choose this endpoint when you need historical order book depth data over time for a specific Deepstate market — particularly for building heatmaps, identifying liquidity clusters, analyzing price-level support/resistance, or monitoring how resting order distribution has evolved. This is the right choice for time-series depth analysis rather than a point-in-time snapshot. Prefer this over live order book endpoints when you need a look-back window of hours or days at 1h or 1d resolution.
Side effects
- Missing required 'book' parameter returns a validation error
- Invalid resolution value (not '1h' or '1d') returns an enum validation error
- Invalid side value (not 'bid' or 'ask') returns an enum validation error
- Unknown or unsupported book ID returns empty results or a 404
- Time range too broad for the selected resolution may result in large payloads or truncation
- Payment failure or missing x402 payment header returns a 402 Payment Required response
- Future 'to' date beyond chain head returns no data or partial results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"to": "2026-09-02T16:00:00Z",
"from": "2026-09-02T15:00:00Z",
"points": [
{
"side": "bid",
"bucket": "2026-09-02T15:00:00Z",
"finality": "safe",
"size_raw": "5213000000",
"price_raw": "216.480000000000000000",
"order_count": 4,
"block_number": 52661600,
"market_session": "regular",
"denominated_order_count": 4
},
{
"side": "ask",
"bucket": "2026-09-02T15:00:00Z",
"finality": "safe",
"price_raw": "220.480000000000000000",
"order_count": 3,
"block_number": 52661600,
"market_session": "regular",
"denominated_order_count": 0
}
],
"book_id": "0xdf941c235503a5d2e67aee5dea00f2965f99421c0d034bd77f924c05c66bf399",
"coverage": {
"order_count": 253,
"denominated_order_count": 129
},
"book_slug": "NVDA-USDG",
"book_label": "NVDA/USDG",
"resolution": "1h",
"size_token": {
"symbol": "USDG",
"address": "0x5fc5360D0400a0Fd4f2af552ADD042D716F1d168",
"decimals": 6
}
}
}Tags
x402
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