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Time Series Completeness — IQR Outlier Flags + Keyed Dataset Comparison
x402
Time Series Completeness — IQR Outlier Flags + Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Analyzes time series completeness records (observed vs expected data points) using IQR-based outlier detection and keyed dataset comparison, producing two independent analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — IQR outlier flags + Keyed dataset comparison: IQR outlier flags + Keyed dataset comparison for supplied time series completeness records (observed_points, expected_points). 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 reports: (1) an IQR outlier detection report that flags rows where the selected field (observed_points or expected_points) falls outside the interquartile range boundaries, and (2) a keyed dataset comparison report that matches rows by row_id across the primary and secondary datasets and identifies differences. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Pipeline completeness anomaly detection
“I have daily logs of how many data points my ETL pipeline observed vs expected for each dataset group — can you flag which dates are IQR outliers in observed_points and also compare this week's run against last week's run row by row?”
Cross-environment data collection audit
“We collect sensor readings in two environments and I want to check if the observed point counts are consistent — run IQR outlier flagging on the primary environment's records and compare them against the secondary environment's records using the row IDs as keys.”
Data feed completeness regression check
“After our feed provider changed something, I need to compare yesterday's completeness records against the baseline from two weeks ago — flag any IQR outliers in expected_points and show me which row_ids differ between the two datasets.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-179?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both IQR-based outlier detection and a keyed dataset comparison in a single low-cost call ($0.01 USDC) on pre-collected time series completeness records. It is ideal for data quality pipelines that track observed vs expected data point counts per date and group. Prefer this over separate analysis tools when your dataset fits within 200 rows and you want two complementary views — statistical outlier flagging plus record-level cross-dataset diffing — without sending data to an external live system.
Side effects
- Fewer than 1 row supplied — rejected by minItems constraint
- More than 200 rows supplied — rejected by maxItems constraint
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) on any row — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- row_id longer than 80 characters — rejected
- IQR computation may be unreliable with very few rows (e.g. fewer than 4–5 data points)
- Payment failure via x402 protocol — endpoint not invoked
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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