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Null Coverage Duplicate Key Report + Base-100 Series Analyzer
x402
Null Coverage Duplicate Key Report + Base-100 Series Analyzer is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).
Generates two local analytical reports — a duplicate key report and a base-100 indexed series — for user-supplied null coverage records containing missing and total value counts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Duplicate key report + Base-100 series: Duplicate key report + Base-100 series for supplied null coverage records (missing_values, total_values). 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 duplicate key report identifying any repeated row_id values across the supplied rows, and (2) a base-100 indexed series for the selected numeric field (missing_values or total_values) anchored at the specified base_index row. Both reports are computed locally from the supplied data with no external lookups. Up to 200 rows are supported per call.
Example use cases
Data pipeline duplicate key audit
“I have a batch of null coverage records from our ETL pipeline and I need to know if any row IDs are duplicated — can you run a duplicate key report on these rows: row-A on 2025-01-10 in group-sales with 5 missing out of 100 total, row-B on 2025-01-11 in group-sales with 5 missing out of 100 total, row-A on 2025-01-12 in group-ops with 8 missing out of 50 total? Use missing_values as the field and start the index at 0.”
Monthly completeness trend indexing
“Can you generate a base-100 series for my monthly data completeness records so I can see how total_values have changed relative to the first month? Here are the rows: jan on 2025-01-01 in group-finance with 200 missing out of 5000 total, feb on 2025-02-01 in group-finance with 180 missing out of 5200 total, mar on 2025-03-01 in group-finance with 150 missing out of 5100 total. Field should be total_values, base index at 0.”
Multi-group null coverage QA check
“I'm doing a quality audit across two dataset groups and need both a duplicate key check and a normalized index series — please analyze these 5 records: r1 on 2024-06-01 group-alpha 12 missing 300 total, r2 on 2024-06-02 group-beta 7 missing 280 total, r3 on 2024-06-03 group-alpha 15 missing 310 total, r1 on 2024-06-04 group-beta 9 missing 290 total, r5 on 2024-06-05 group-alpha 11 missing 305 total. Use missing_values, starting the base-100 index at position 0.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-063?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a duplicate key audit and a base-100 normalization series on null coverage data in a single cheap call ($0.01 USDC). It is ideal for data quality workflows where you want to verify row uniqueness and trend-index completeness metrics simultaneously, without any external data fetching or prediction. Best suited for batches of up to 200 rows of time-series null coverage records organized by dataset group.
Side effects
- Missing required fields (row_id, date, missing_values, total_values) causes validation failure
- Submitting more than 200 rows exceeds the maxItems limit and is rejected
- Invalid date format (not YYYY-MM-DD) causes a pattern validation error
- base_index out of range (>= number of submitted rows) may produce undefined indexing behavior
- Null or negative values for total_values or missing_values are accepted but may produce unexpected base-100 results
- Empty rows array (minItems:1 violated) returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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