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Article Publication Data Quality Audit, String Normalisation & Numeric Interval Filter
x402
Article Publication Data Quality Audit, String Normalisation & Numeric Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Runs three analytical reports on article publication records: record quality audit, string normalisation, and numeric interval filtering for published_articles or word_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Article publication — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied article publication records (published_articles, word_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 per call: (1) a record quality audit highlighting missing, malformed, or invalid values across the supplied rows; (2) a string normalisation report showing standardised forms of channel_group and other string fields; (3) a numeric interval filter report listing which rows fall within or outside the specified minimum–maximum range for the chosen numeric field (published_articles or word_count). Covers up to 200 rows per call.
Example use cases
Pre-load data quality check for CMS
“Before I load this batch of 80 article publication records into the CMS, can you run a full quality audit, normalise the channel_group strings, and filter out any rows where published_articles falls outside 1 to 500? Here are the rows with row_id, channel_group, date, published_articles, and word_count.”
Editorial team word count compliance audit
“I need to check our editorial team's output data for the last quarter — can you audit data quality, normalise the channel group names, and flag any articles where word_count is outside the range 400 to 8000? I'll supply the rows.”
News channel performance data cleaning
“We have about 120 rows of daily news channel data with published_articles and word_count columns. Can you run the three-report analysis — quality audit, string normalisation, and a numeric interval filter on published_articles between 5 and 200 — so we can clean it up before analysis?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-01-197?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined data quality audit, string normalisation, and numeric range filter on article publication records in a single low-cost call. It is ideal for pre-processing editorial or news publishing datasets before loading into analytics pipelines, dashboards, or data warehouses. Prefer it over generic validation tools when your data specifically contains published_articles and word_count fields with channel_group categorical dimensions.
Side effects
- More than 200 rows submitted — API rejects with validation error
- Missing required fields (row_id, channel_group, date, published_articles, word_count) cause row-level rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Minimum value greater than maximum value may produce empty filter results
- Invalid field enum value (not published_articles or word_count) causes request rejection
- Payment not attached or insufficient USDC causes 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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