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Comment Inventories: Record Quality Audit + String Normalisation + Numeric Row Ordering
x402
Comment Inventories: Record Quality Audit + String Normalisation + Numeric Row Ordering 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).
Audits data quality, normalises strings, and sorts rows numerically for up to 200 comment inventory records containing comment_count and unique_author_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Comment inventories — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied comment inventories records (comment_count, unique_author_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent analytical reports generated locally: (1) a record quality audit flagging issues in the supplied rows, (2) a string normalisation report for text fields like channel_group, and (3) a numeric row ordering report sorting rows by the selected field (comment_count or unique_author_count). No external data is fetched or predicted.
Example use cases
Community engagement data cleanup
“I have a dataset of daily comment counts and unique author counts across different channel groups and I want to check data quality, normalise the channel group names, and sort rows by comment_count — can you run all three reports on it?”
Author count ordering for editorial review
“Please audit the quality of my comment inventory records, normalise any string fields, and order the rows numerically by unique_author_count — here are my 80 rows with row_id, date, channel_group, comment_count, and unique_author_count.”
Pre-reporting data validation for comment metrics
“Before I put together my monthly report I need to validate this comment inventory dataset — run the record quality audit, string normalisation, and numeric ordering on these rows so I can catch any issues in the comment_count figures.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-16-196?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled local analytical operations — quality audit, string normalisation, and numeric ordering — on comment inventory data (comment_count, unique_author_count) in a single low-cost call. Ideal for pre-processing comment engagement datasets before reporting or downstream analysis, when no live lookups or predictions are needed and data stays within the supplied rows (up to 200).
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, channel_group, comment_count, unique_author_count) causes rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Numeric values outside allowed range cause input rejection
- Empty rows array is rejected (minItems: 1)
- Invalid field enum value (not comment_count or unique_author_count) causes error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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