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Water Service Coverage Record Quality Audit & String Normalisation
x402
Water Service Coverage Record Quality Audit & String Normalisation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).
Audits water service coverage records for quality issues and normalises region/date strings, producing two independent reports for up to 200 rows of household data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Water service coverage — Record quality audit + String normalisation: Record quality audit + String normalisation for supplied water service coverage records (served_households, total_households). 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
Two independent analytical reports: (1) a record quality audit identifying issues such as null values, impossible ratios (served > total households), out-of-range numbers, malformed dates, and missing fields across up to 200 rows; (2) a string normalisation report showing standardised/cleaned versions of region and date string fields. Reports are generated locally with no external lookups or live data access.
Example use cases
Municipal water audit before reporting
“I need to quality-check our quarterly water service coverage data before submitting to the regulator — can you run a record quality audit and string normalisation on these 50 rows? Each row has a row_id, region name, date, served_households, and total_households.”
Detect impossible coverage ratios
“Some of our water coverage records look off — served_households is higher than total_households in several rows. Can you audit these 120 records for data quality problems and flag anything that looks wrong?”
Normalise region strings across datasets
“We merged water coverage data from three field teams and the region names are inconsistently formatted — things like 'North Zone', 'north-zone', and 'NORTH ZONE'. Can you run string normalisation on these 80 rows so we have consistent region labels?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-19-001?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have water service coverage tabular data (served_households, total_households per region and date) and need both a data quality audit and string normalisation in a single low-cost call. It is purpose-built for water utility/infrastructure coverage records specifically, as opposed to generic CSV validators. Best when batch processing up to 200 rows in one shot at fixed cost.
Side effects
- Input array is empty (minItems:1 violation) — request rejected
- More than 200 rows submitted (maxItems:200 violation) — request rejected
- Row missing required fields (row_id, region, date, served_households, total_households) — validation error
- Date string not matching YYYY-MM-DD pattern — row-level error flagged
- Numeric values outside allowed range (-1T to +1T) — schema rejection
- Payment not provided or insufficient (x402 protocol) — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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