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Dataset Partition Sizes — Duplicate Key Report + IQR Outlier Flags
x402
Dataset Partition Sizes — Duplicate Key Report + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).
Analyzes up to 200 dataset partition size records to produce a duplicate key report and IQR-based outlier flags for row_count or file_mb fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset partition sizes — Duplicate key report + IQR outlier flags: Duplicate key report + IQR outlier flags for supplied dataset partition sizes records (row_count, file_mb). 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 partition records, and (2) IQR outlier flags marking records whose chosen metric (row_count or file_mb) falls outside the interquartile range. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Data pipeline partition quality audit
“I have 50 partition records from our nightly ETL pipeline — each with a row_id, dataset_group, date, row_count, and file_mb. Can you run a duplicate key check and flag any IQR outliers on the row_count field so I can catch bad partitions before we load to the warehouse?”
Storage anomaly detection in file sizes
“Can you analyze these dataset partition records for duplicate keys and flag any file_mb values that are IQR outliers? I want to spot partitions that are unusually large or small compared to the rest of the group.”
Pre-merge data integrity check
“Before I merge these 120 dataset partition records, check them for any duplicate row_id entries and flag which partitions have row_count values that fall outside the IQR range — I want to catch data quality issues early.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-07-065?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local duplicate-key detection and IQR-based outlier flagging specifically for dataset partition size records (row_count and file_mb). It is ideal for data engineering workflows where you want a quick, cheap ($0.01 USDC) quality check on up to 200 partition records without sending data to a full analytics platform. Prefer this over general-purpose analytics APIs when you need both duplicate detection and statistical outlier flagging in a single call on structured partition metadata.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — request rejected
- Invalid date format (must match YYYY-MM-DD) — validation error
- Missing required fields (row_id, dataset_group, date) — schema validation failure
- Invalid field enum value (must be row_count or file_mb) — error response
- Null numeric values may affect IQR computation if too many are null
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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