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Translation Delivery Analytics — Adjacent Row Changes & IQR Outlier Flags
x402
Translation Delivery Analytics — Adjacent Row Changes & 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 2026-10-26).
Analyzes translation delivery records by computing adjacent row-to-row changes and flagging IQR-based outliers for translated_words or source_words across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Translation delivery — Adjacent row changes + IQR outlier flags: Adjacent row changes + IQR outlier flags for supplied translation delivery records (translated_words, source_words). 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 analytical reports: (1) adjacent row-to-row changes for the selected field (translated_words or source_words), showing delta values between consecutive records; and (2) IQR-based outlier flags identifying rows whose values fall outside the interquartile range bounds. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Spike detection in weekly translation output
“I have 80 rows of weekly translation delivery data with translated_words and source_words by document group and date — can you run the adjacent row change and IQR outlier analysis on translated_words to see if any weeks had unusual spikes or drops?”
Quality audit of localization vendor records
“I need to audit our localization vendor's delivery logs for anomalies. Here are 120 records with row IDs, document groups, dates, and word counts — please flag any rows where source_words look like outliers using the IQR method and also show me the adjacent row changes.”
Monitoring translation throughput across document groups
“Can you analyze these 40 translation delivery records across our 'legal', 'marketing', and 'support' document groups and tell me which rows have the biggest jumps in translated_words from one row to the next, and which ones are flagged as IQR outliers?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-writing-04-157?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local statistical analysis of translation delivery records without any external data enrichment or ML predictions. Ideal for auditing word count time series for anomalies (IQR outliers) and sequential volatility (adjacent row changes) in a single low-cost call. Best suited for datasets up to 200 rows where both outlier flagging and change detection are needed simultaneously.
Side effects
- Fewer than 1 or more than 200 rows supplied — request rejected
- Missing required fields (row_id, document_group, date, translated_words, source_words) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- field enum value not 'translated_words' or 'source_words' — rejected
- Null values in the selected numeric field may affect IQR and delta calculations
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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