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Join Coverage Analytics: Record Quality Audit, Exact Row Deduplication & Daily Sum Series
x402
Join Coverage Analytics: Record Quality Audit, Exact Row Deduplication & Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Runs three analytical reports (record quality audit, exact row deduplication, and daily sum series) on supplied join coverage data (matched_rows, source_rows) for up to 200 rows using local analytical engines.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Record quality audit + Exact row deduplication + Daily sum series: Record quality audit + Exact row deduplication + Daily sum series for supplied join coverage records (matched_rows, source_rows). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent analytical reports returned together: (1) a record quality audit summarizing data completeness and anomalies across supplied rows, (2) an exact row deduplication report identifying and flagging duplicate records, and (3) a daily sum series aggregating the selected field (matched_rows or source_rows) by date — all computed locally against the supplied data with no external lookups.
Example use cases
ETL join output quality check
“I have about 50 join coverage records from my ETL pipeline across two dataset groups — can you run a record quality audit, deduplicate exact duplicate rows, and give me a daily sum series for matched_rows so I can spot anomalies?”
Deduplicating multi-group coverage data
“My join coverage dataset has rows for group-a and group-b from the past month and I suspect there are exact duplicates — can you run the deduplication report and the quality audit on all 120 rows using the source_rows field?”
Daily aggregation for coverage reporting
“I need to produce a daily sum series for matched_rows across my join coverage records for October 2026 — run all three reports on my 80-row dataset so I also get the quality and deduplication summaries alongside the daily totals.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-215?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 join coverage records and need all three of a quality audit, deduplication check, and daily aggregation in a single low-cost call. It is ideal for ETL pipeline validation, data engineering QA, and coverage reporting workflows where you supply the data locally and need no external enrichment or prediction — just fast, deterministic analytical reports on matched_rows and source_rows.
Side effects
- More than 200 rows supplied — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Numeric values outside the allowed range cause rejection
- Empty rows array returns an error
- Field enum value other than 'matched_rows' or 'source_rows' is rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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