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Internal Support — String Normalisation + IQR Outlier Flags
x402
Internal Support — String Normalisation + 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 2026-10-25).
Normalises strings and flags IQR-based outliers in internal support records (responded_requests, received_requests) for up to 200 rows, producing 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Internal support — String normalisation + IQR outlier flags: String normalisation + IQR outlier flags for supplied internal support records (responded_requests, received_requests). 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 string normalisation report standardising text fields such as team_group across the supplied rows, and (2) an IQR outlier flag report identifying statistical anomalies in the selected numeric field (responded_requests or received_requests) using interquartile range methodology. Results cover up to 200 input rows with no external lookups or predictions.
Example use cases
Outlier detection in daily support volume
“I have 30 days of support data across two teams with responded_requests and received_requests per day — can you normalize the strings and flag any IQR outliers in responded_requests so I can spot which days had abnormal activity?”
Support team data quality audit
“My internal support CSV has team_group names that might be inconsistently formatted and some weird spikes in received_requests — can you normalize the strings and run IQR outlier detection on received_requests across all 120 rows?”
Multi-team response rate anomaly report
“We track responded_requests and received_requests by team every day. Can you take these 80 rows, clean up the string fields, and produce both the normalisation and IQR outlier flag reports for responded_requests?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-22-032?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local statistical analysis on internal support operations data — specifically string normalisation combined with IQR-based outlier detection — without any external lookups, ML predictions, or live data sources. Ideal for batch-processing up to 200 rows of team support metrics at minimal cost ($0.01 USDC for two reports). Not suitable for real-time monitoring, predictive analytics, or datasets exceeding 200 rows.
Side effects
- Input exceeds 200 rows — request rejected with validation error
- Missing required fields (row_id, date, team_group, responded_requests, received_requests) cause row-level errors
- Invalid date format (not YYYY-MM-DD) causes parsing failure
- Numeric values outside allowed range trigger validation errors
- Field selector not matching enum values ('responded_requests' or 'received_requests') causes schema rejection
- Insufficient data points for meaningful IQR computation may produce degenerate outlier flags
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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