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Exchange Quote Quality Audit & IQR Outlier Flagging
x402
Exchange Quote Quality Audit & IQR Outlier Flagging is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).
Performs a data quality audit and IQR-based outlier detection on up to 200 exchange quote records (bid/ask prices), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Exchange quote observations — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied exchange quote observations records (bid_price, ask_price). 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
Two independent analytical reports: (1) a record quality audit covering issues such as nulls, format violations, and consistency problems across the supplied bid_price and ask_price fields; (2) IQR outlier flags identifying which rows fall outside interquartile range thresholds for the selected price field, with row-level identifiers.
Example use cases
Pre-pipeline bid price anomaly check
“Before I feed this batch of 120 exchange quote rows into my pricing model, can you run a quality audit and flag any IQR outliers in the bid_price field? The records span instrument group 'FX-MAJORS' across dates in Q3 2026.”
Ask price data quality review for reporting
“I need a quality audit and outlier report on the ask_price column for these 80 exchange quote observations — instrument group is 'CRYPTO-SPOT', dates run from 2026-09-01 to 2026-09-30. Flag anything that looks like a data error or IQR outlier.”
Multi-instrument quote validation before reconciliation
“Can you check this dataset of 200 exchange quote records for data quality issues and IQR-based outliers in the bid_price? The rows cover two instrument groups, 'RATES-USD' and 'RATES-EUR', with dates throughout November 2026.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-04-014?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local analytical quality checks on batches of exchange quote records (up to 200 rows) without any live market lookup or external data enrichment. It is ideal for pre-processing pipelines that need both a general data quality audit and IQR-based outlier flagging in a single low-cost call. Prefer this over generic statistical tools when your data is structured as bid/ask quote observations with instrument group and date context.
Side effects
- Empty or missing rows array returns validation error
- More than 200 rows submitted exceeds the per-call limit
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Missing required fields (row_id, instrument_group, date) causes rejection
- Null values in both bid_price and ask_price may limit outlier analysis
- Invalid field selector (not 'bid_price' or 'ask_price') causes error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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