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Join Coverage — String Normalisation + Keyed Dataset Comparison
x402
Join Coverage — String Normalisation + Keyed Dataset Comparison 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 metrics (matched_rows, source_rows) across two datasets using string normalization and keyed comparison, producing 2 analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison 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 independent analytical reports: (1) a string normalization report covering the supplied join coverage data and (2) a keyed dataset comparison report contrasting the primary (rows) and secondary (other) datasets across matched_rows and source_rows, grouped by row_id, dataset_group, and date. No external lookups are performed; all analysis is local.
Example use cases
ETL pipeline join quality audit
“I just ran an ETL pipeline and I need to check how well my fact table joined to the dimension table. I have 80 rows with row_id, dataset_group, date, matched_rows, and source_rows for both the before and after datasets — can you run a string-normalized keyed comparison and give me both reports so I can spot where the join coverage dropped?”
Cross-team dataset reconciliation
“Our analytics team and the data engineering team have different snapshots of the same join results — can you compare them using string normalization and keyed dataset comparison? I have about 120 rows in each dataset with row_id, dataset_group, date, matched_rows, and source_rows, and I want to see where the numbers diverge across groups.”
Daily join coverage trend check
“I want to audit my join coverage metrics for October — I have two sets of daily records (about 30 rows each) with row_id, dataset_group, date, matched_rows, and source_rows, and I need a normalized string comparison report plus the keyed dataset diff so I can see if coverage has been consistent day over day.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-036?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to compare two keyed datasets of join coverage metrics (matched_rows vs source_rows) with string normalization applied to keys, and you want two independent analytical reports from a single cheap call. Ideal for data quality engineers validating ETL join completeness, reconciling two snapshots of the same pipeline output, or auditing group-level join rates over time. Prefer this over single-report variants when you need both string normalization insights and keyed comparison in one pass.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) — row-level validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — schema rejection
- Empty rows array — minItems constraint violation
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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