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Join Coverage String Normalisation and Adjacent Row Changes Analyzer
x402
Join Coverage String Normalisation and Adjacent Row Changes Analyzer is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Analyzes join coverage records by performing string normalization and detecting adjacent row changes across matched_rows and source_rows fields, producing 2 analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied join coverage records (matched_rows, source_rows). 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 2 analytical reports per call: (1) a string normalization report covering the dataset_group and row label fields, and (2) an adjacent row changes report highlighting step-changes between consecutive rows in the selected field (matched_rows or source_rows). Reports are generated from the supplied data with no external lookups.
Example use cases
ETL pipeline join quality audit
“I have a week of join coverage data across two dataset groups — the matched_rows went 10, 20, 15, 30, 25 and source_rows went 1, 2, 3, 4, 5. Can you normalize the string labels and flag any sharp adjacent row changes in the matched_rows field so I can spot where the join quality dropped?”
Detecting data drift between source and matched counts
“I'm reviewing daily join metrics for my data warehouse — here are 6 rows across groups 'alpha' and 'beta' with dates from 2026-11-01 to 2026-11-06. Run string normalization and detect adjacent row changes on the source_rows field so I can see where upstream volume shifted suddenly.”
Dataset group consistency check for reporting
“Before I publish my monthly join coverage report, can you run string normalization and adjacent row changes detection on these 8 rows across groups 'us-east', 'us-west', and 'eu-central', using the matched_rows field? Dates run from 2026-09-01 to 2026-09-08.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-029?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local analytical processing of join coverage tabular data — specifically string normalization of group labels and adjacent row change detection — without requiring external data sources, live lookups, or predictions. Ideal for ETL quality checks, data pipeline audits, and pre-report data validation on small to medium datasets (up to 200 rows).
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — validation error
- Empty rows array (minItems:1 not satisfied) — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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