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Join Coverage — Keyed Dataset Comparison with Missing-Value Fill
x402
Join Coverage — Keyed Dataset Comparison with Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Compares two keyed datasets on matched_rows or source_rows metrics, filling explicit missing values and producing two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Keyed dataset comparison + Explicit missing-value fill: Keyed dataset comparison + Explicit missing-value fill 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
Two independent analytical reports comparing the two supplied keyed datasets on the selected field (matched_rows or source_rows), with explicit missing-value fills applied where nulls are present, covering up to 200 rows per dataset. No live lookups or external data is used — all analysis is performed on the supplied data using local analytical engines.
Example use cases
ETL pipeline join audit
“I have two snapshots of my ETL join output for October — the first run has matched_rows counts per dataset_group and date, and the second run has slightly different counts for some rows. Can you compare them on the matched_rows field, fill any nulls explicitly, and give me a coverage report showing where the discrepancies are?”
Source row completeness check
“My data team ran two versions of a join between our customer table and transaction table, and I need to compare source_rows counts across group-a and group-b for last week. Please compare the two datasets, explicitly fill any missing source_rows values, and give me 2 analytical reports on the coverage differences.”
Dataset group coverage tracking
“I want to track join coverage trends across my dataset groups — I have two sets of up to 200 rows each with row_id, dataset_group, date, matched_rows, and source_rows. Compare them on the matched_rows field, fill in missing values where they appear, and produce 2 independent coverage comparison reports.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-190?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to compare two keyed datasets specifically on join coverage metrics (matched_rows or source_rows) with explicit missing-value handling, across up to 200 rows, and want two independent analytical reports from local engines without any external lookups or live data. Prefer it over generic analytics tools when the data is already structured with row_id, dataset_group, and date keys and you need a lightweight, pay-per-call comparison with null-fill logic built in.
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, dataset_group, date) in any row — validation error
- Invalid date format (must be YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — rejection
- Empty rows array (minItems: 1 violated) — error
- Field enum value not matched_rows or source_rows — schema error
- Payment of 0.01 USDC not completed — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array | |
| method | string |
Tags
x402
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