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Publication Proofing — Secondary-Measure Weighted Mean + Date by Category Pivot
x402
Publication Proofing — Secondary-Measure Weighted Mean + Date by Category Pivot 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).
Computes a secondary-measure weighted mean and a date-by-category pivot table for supplied publication proofing records (checked_pages, flagged_pages) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Publication proofing — Secondary-measure weighted mean + Date by category pivot: Secondary-measure weighted mean + Date by category pivot for supplied publication proofing records (checked_pages, flagged_pages). 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) a secondary-measure weighted mean (e.g. flagged_pages weighted by checked_pages) across all supplied rows, and (2) a date-by-category pivot table showing the selected metric broken down by date and document_group. Results are computed locally from supplied data with no external lookups.
Example use cases
Editorial error rate analysis by group
“I have proofing logs for 4 document groups over the past month — each row has a date, document_group, checked_pages, and flagged_pages. Can you compute the weighted mean of flagged_pages and pivot the data by date and category so I can see error trends?”
Daily QA dashboard for publication team
“We track checked_pages and flagged_pages daily across groups like 'legal', 'marketing', and 'editorial'. Can you run a date-by-category pivot and a weighted mean on our latest 150 proofing rows using flagged_pages as the measure?”
Comparing proofing quality across document batches
“I've got 80 proofing records split across two document groups — group-a and group-b — each with dates, checked_pages, and flagged_pages. Run the secondary-measure weighted mean and date pivot so I can compare which group has the higher error rate.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-writing-18-185?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 publication proofing records with checked_pages and flagged_pages and need both a weighted mean analysis and a date-by-category pivot in a single call. It is ideal for editorial QA workflows where you want two distinct analytical views on the same dataset without external data access or ML predictions.
Side effects
- Missing required fields (row_id, document_group, date, checked_pages, flagged_pages) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Submitting more than 200 rows exceeds the row limit and will be rejected
- Null values in both checked_pages and flagged_pages may produce undefined weighted mean results
- Invalid field enum value (anything other than 'checked_pages' or 'flagged_pages') causes an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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