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Rainfall Observations — Duplicate Key Report + Numeric Row Ordering
x402
Rainfall Observations — Duplicate Key Report + Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Analyzes supplied rainfall observation records to identify duplicate keys and produce a numerically ordered ranking of rows by a chosen field (rainfall_mm or duration_hours), returning two reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Rainfall observations — Duplicate key report + Numeric row ordering: Duplicate key report + Numeric row ordering for supplied rainfall observations records (rainfall_mm, duration_hours). 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 structured reports: (1) a duplicate key report identifying any rows with repeated identifiers across the supplied dataset, and (2) a numeric row ordering ranking all supplied rows by the chosen field (rainfall_mm or duration_hours), covering up to 200 input rows.
Example use cases
Audit rain gauge data for duplicates
“I have a batch of 50 rainfall observation records from our monitoring network — can you run a duplicate key check on them to flag any rows that share the same row_id, and also rank all the rows by rainfall_mm so I can see which stations recorded the most rain?”
Rank weather station readings by duration
“I've collected hourly rainfall logs from several station groups over the past month. Can you order all these rows numerically by duration_hours and also tell me if any row IDs are repeated in the dataset?”
Pre-import data quality check for hydrology pipeline
“Before I import these 120 rainfall records into our database, can you check them for duplicate keys and give me a numeric ordering by rainfall_mm so I can spot anomalies? I'll paste the rows with their row_id, station_group, date, rainfall_mm, and duration_hours fields.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-02-058?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need offline, deterministic data-quality analysis on rainfall observation records — specifically a duplicate key check and a numeric field sort — without any live weather lookup, prediction, or external data enrichment. Best suited for pre-import audits, data pipeline validation, or batch QA on station-group rainfall logs of up to 200 rows.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, rainfall_mm, duration_hours) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Null values in the selected numeric field may affect ordering output
- Empty rows array (minItems:1 not met) causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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