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Join Coverage String Normalisation and Duplicate Key Report
x402
Join Coverage String Normalisation and Duplicate Key Report 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).
Analyzes join coverage records (matched_rows, source_rows) to produce string normalisation and duplicate key reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — String normalisation + Duplicate key report: String normalisation + Duplicate key report 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 two independent analytical reports: (1) a string normalisation report flagging inconsistent or unnormalised string values across the supplied rows, and (2) a duplicate key report identifying any duplicate row_id or key combinations within the up to 200 provided join coverage records.
Example use cases
ETL pipeline join audit
“I just ran an ETL join between my orders and customers tables and I want to check for duplicate keys and any string normalisation issues — here are my 50 coverage rows with row IDs, dataset groups, dates, and matched vs source counts. Can you run the two reports?”
Data quality check before merge
“Before I merge these two datasets, can you analyze my join coverage records for duplicate row keys and flag any string normalisation problems? I have 120 rows across groups alpha and beta, dated from 2025-01-01 to 2025-04-30.”
Detecting duplicate keys post-join
“My join result looks off — can you run a duplicate key report on these 30 coverage rows from dataset group 'sales-2024' to see if any row IDs are duplicated, and also give me the string normalisation report?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-021?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, offline (no external lookup) string normalisation and duplicate key detection specifically for join coverage records with matched_rows and source_rows metrics. It is ideal for data quality audits in ETL pipelines, pre-merge checks, or post-join validation when you have up to 200 rows and want both reports in a single low-cost call.
Side effects
- More than 200 rows supplied — request will be rejected or truncated
- Missing required fields (row_id, date, dataset_group, 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) — schema rejection
- Empty rows array — minimum 1 item required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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