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Sampling Observations — String Normalisation + Adjacent Row Changes
x402
Sampling Observations — String Normalisation + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Normalises string fields and detects adjacent row changes in sampling observation records (sample_value, sample_weight) for up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied sampling observations records (sample_value, sample_weight). 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 analytical reports: one covering string normalisation of text fields (e.g. dataset_group) across the submitted rows, and one identifying adjacent row-to-row changes in the specified numeric field (sample_value or sample_weight). Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Survey data string cleanup and change detection
“I have 50 rows of survey sampling observations with messy dataset_group labels and I need to normalize those strings and also flag wherever the sample_value changes between adjacent rows — dates run from 2025-01-01 to 2025-02-19, field is sample_value. Can you run both reports?”
Lab sample weight shift monitoring
“I've got 120 lab sampling records from 2024-06-01 through 2024-10-28 across two groups, control and treatment, and I need to normalize the group name strings and identify any adjacent row changes in sample_weight. Please run both analytical reports on the sample_weight field.”
Retail inventory sample QA before ingestion
“Before I ingest my retail sampling observations into our pipeline, can you normalize all the string fields and detect adjacent row changes in sample_value? I'll send you up to 80 rows with row IDs, dates, dataset_group names, sample_value, and sample_weight.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-029?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need both string normalisation and adjacent row change detection on sampling observation records in a single call for up to 200 rows. Prefer it over general-purpose analytics when your data specifically carries sample_value and sample_weight fields and you want two focused reports without external lookups or live data enrichment.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) causes rejection
- Dates not matching YYYY-MM-DD pattern fail schema validation
- row_id exceeding 80 characters is rejected
- Numeric values outside ±1,000,000,000,000 fail schema constraints
- Empty rows array (minItems:1 not met) returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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