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Reservoir Observations — Record Quality Audit + Grouped Numeric Summary
x402
Reservoir Observations — Record Quality Audit + Grouped Numeric Summary is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Runs two analytical reports on supplied reservoir observation rows: a record quality audit and a grouped numeric summary of stored_m3 or capacity_m3 values, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Reservoir observations — Record quality audit + Grouped numeric summary: Record quality audit + Grouped numeric summary for supplied reservoir observations records (stored_m3, capacity_m3). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two reports: (1) a record quality audit identifying issues such as missing values, out-of-range figures, or malformed dates across the supplied rows; and (2) a grouped numeric summary (e.g. min, max, mean, count) for the selected numeric field (stored_m3 or capacity_m3), aggregated by station_group.
Example use cases
Water authority daily data validation
“I just exported 120 reservoir observation records from our monitoring system with stored_m3 and capacity_m3 readings across 8 station groups — can you run a quality audit to flag bad records and give me a grouped numeric summary of stored_m3 by station group?”
Pre-analysis data hygiene check
“Before I run my hydrological model, can you check these 80 reservoir rows for data quality issues and also summarize the capacity_m3 values grouped by station so I can spot any outliers?”
Monthly reservoir reporting
“I need two quick reports on this month's reservoir data — a record quality audit and a grouped summary of stored_m3 by station group — I have 45 rows covering three reservoir sites.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-19-005?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw reservoir observation data (stored_m3, capacity_m3) and need both a data quality audit and a grouped numeric summary in a single low-cost call, without requiring external lookups, live sensor feeds, or predictive modeling. It is ideal for pre-processing pipelines, reporting workflows, or data validation steps before feeding data into downstream hydrological models.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, station_group, date, stored_m3, capacity_m3) cause validation errors
- Invalid date format (non-YYYY-MM-DD) triggers schema rejection
- All-null numeric fields may produce empty or degenerate summary statistics
- Submitting zero rows returns an error due to minItems:1 constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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