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Schema Conformity IQR Outlier Flags + Keyed Dataset Comparison
x402
Schema Conformity 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 2026-10-14).
Runs two local analytical reports on schema conformity data: IQR-based outlier detection and keyed dataset comparison for valid_records or checked_records fields, up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Schema conformity — IQR outlier flags + Keyed dataset comparison: IQR outlier flags + Keyed dataset comparison for supplied schema conformity records (valid_records, checked_records). 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) IQR-based outlier flags indicating which rows fall outside the interquartile range for the selected field (valid_records or checked_records), and (2) a keyed dataset comparison report showing differences between the primary and secondary datasets matched by row_id. No external lookups or predictions are made; all computation is local.
Example use cases
Data pipeline conformity audit
“I have two sets of schema conformity logs from our ETL pipeline — a baseline and a current run, each with about 80 rows containing row_id, dataset_group, date, valid_records, and checked_records. Can you run IQR outlier flagging on valid_records and compare the two datasets by key to see what changed?”
Detect anomalous checked_records counts
“Here are 120 rows of daily schema conformity data across several dataset groups. Can you flag any rows where checked_records looks like a statistical outlier using IQR, and also compare this dataset against last week's snapshot by row_id?”
Weekly data quality regression check
“We run weekly schema validation and I want to compare this week's conformity records against last week's — about 60 rows each — and flag any rows where valid_records has gone outside the IQR range so I can investigate regressions.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-02-179?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both IQR-based statistical outlier detection AND a keyed side-by-side dataset comparison on schema conformity data (valid_records, checked_records) in a single call for up to 200 rows. It is purpose-built for data quality monitoring workflows where you already have the data locally and need no external lookup, prediction, or live data fetching. Prefer it over generic stats tools when your data fits the schema conformity domain with dataset_group and date dimensions.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds limit
- Missing required fields (row_id, date, valid_records, checked_records) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema rejection
- Null values in numeric fields may affect IQR computation
- Mismatched row_ids between primary and secondary datasets result in unmatched keys in comparison report
- Payment of 0.01 USDC not included — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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