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Newsletter Observations — Record Quality Audit + Adjacent Row Changes
x402
Newsletter Observations — Record Quality Audit + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).
Runs two local analytical reports (record quality audit and adjacent row change detection) on up to 200 newsletter observation rows containing delivered_messages and open_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Newsletter observations — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes for supplied newsletter observations records (delivered_messages, open_count). 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 flagging issues such as nulls, out-of-range values, or formatting problems in each row's delivered_messages or open_count fields; and (2) an adjacent row change report identifying significant value shifts between consecutive rows for the selected field. Both reports cover up to 200 supplied rows and are computed locally without external lookups.
Example use cases
Pre-send newsletter data validation
“Before I load my newsletter metrics into our dashboard, can you audit this batch of up to 150 newsletter observation rows for quality issues in the delivered_messages field? I need to catch any bad records and see where values jump unexpectedly between adjacent rows.”
Detecting open rate anomalies in campaign data
“I've got a CSV of newsletter observations with open_count and delivered_messages across different channel groups and dates — can you run the quality audit and adjacent row change report on the open_count field so I can find where counts shift suspiciously between rows?”
Channel group data consistency check
“We're comparing newsletter performance across channel groups and I need to check about 200 rows of observation data for record quality issues and sudden changes in delivered_messages between consecutive rows before we present the numbers to the team.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-08-011?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular newsletter observation data (delivered_messages, open_count) and need two specific local analytical reports — a record quality audit and an adjacent row change detection — without any live lookups, predictions, or external actions. It is well-suited for pre-processing pipelines that need cheap, fast, offline data quality checks on small-to-medium newsletter datasets (up to 200 rows) at $0.01 per call.
Side effects
- More than 200 rows submitted — request exceeds maxItems limit
- Missing required fields (row_id, channel_group, date, delivered_messages, open_count) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema rejection
- Field selector not one of 'delivered_messages' or 'open_count' — enum validation failure
- Empty rows array — minItems constraint violation
- Payment failure or insufficient USDC balance — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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