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Null Coverage Analytics — Numeric Row Ordering & Adjacent Row Changes
x402
Null Coverage Analytics — Numeric Row Ordering & Adjacent Row Changes 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).
Analyzes null coverage records (missing_values, total_values) for numeric row ordering anomalies and adjacent row-to-row changes across up to 200 rows, producing two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Numeric row ordering + Adjacent row changes: Numeric row ordering + Adjacent row changes 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: one covering numeric row ordering of the selected field (missing_values or total_values) across the supplied rows, and one covering adjacent row-to-row changes in that field. Reports are generated locally with no external lookups.
Example use cases
Detect ordering gaps in daily data quality logs
“I have daily null coverage stats for two dataset groups across October — can you check whether the missing_values field is in proper numeric row order and flag any big jumps between adjacent rows? Here are my 5 rows: row-1 (group-a, 2026-10-01, missing=5, total=100), row-2 (group-a, 2026-10-02, missing=8, total=100), row-3 (group-a, 2026-10-03, missing=3, total=100), row-4 (group-a, 2026-10-04, missing=22, total=100), row-5 (group-a, 2026-10-05, missing=21, total=100).”
Spot sudden changes in total values across pipeline runs
“Run the row ordering and adjacent change analysis on my total_values field for these pipeline run records — row-1 (pipeline-a, 2026-09-01, missing=0, total=500), row-2 (pipeline-a, 2026-09-02, missing=2, total=480), row-3 (pipeline-b, 2026-09-03, missing=1, total=10), row-4 (pipeline-b, 2026-09-04, missing=3, total=495) — and tell me if anything looks out of order or has an unusual adjacent change.”
Audit null rate consistency across dataset groups
“Can you check my null coverage records for numeric ordering issues and adjacent row changes on the missing_values column? I want to audit two groups: row-1 (finance, 2026-11-01, missing=12, total=200), row-2 (finance, 2026-11-02, missing=14, total=200), row-3 (operations, 2026-11-03, missing=45, total=200), row-4 (operations, 2026-11-04, missing=13, total=200), row-5 (finance, 2026-11-05, missing=15, total=200).”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-116?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, on-demand analysis of null coverage data row ordering and sequential row changes without any external lookups or predictions. It is ideal for data quality pipelines that need to detect ordering anomalies and sudden shifts in missing or total value counts across batches of up to 200 rows at minimal cost ($0.01 USDC for two reports).
Side effects
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) causes validation error
- Exceeding 200 rows in the input array returns an error
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Payment not sent or insufficient USDC causes x402 payment required response
- Null values for both missing_values and total_values across all rows may yield empty or degenerate analysis
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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