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Article Publication Data Quality Audit, String Normalisation & Equal-Width Histogram
x402
Article Publication Data Quality Audit, String Normalisation & Equal-Width Histogram 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 local analytical reports — record quality audit, string normalisation, and equal-width histogram — on article publication data (published_articles, word_count) for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Article publication — Record quality audit + String normalisation + Equal-width histogram: Record quality audit + String normalisation + Equal-width histogram 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
Returns three independent analytical reports: (1) a record quality audit flagging missing, malformed, or out-of-range values across up to 200 rows; (2) a string normalisation report on text fields like channel_group; and (3) an equal-width histogram breaking the chosen numeric field (published_articles or word_count) into the specified number of bins with counts per bin.
Example use cases
Editorial data quality check
“I have 120 rows of daily article publication records with channel_group, date, published_articles, and word_count columns — can you audit them for quality issues, normalise the string fields, and give me a 10-bin histogram on the word_count field?”
Distribution analysis for publishing pipeline
“Run a 5-bin equal-width histogram plus a record quality audit on these 80 article publication records I'm uploading — I want to analyse the published_articles field and flag any data problems at the same time.”
Channel group string normalisation check
“I suspect some of my channel_group values have inconsistent formatting across these 200 article rows — can you run string normalisation alongside a quality audit and histogram (using 8 bins) on the published_articles field?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-01-202?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to combine data quality auditing, string normalisation, and distributional analysis on article publication records in a single low-cost call. It is ideal for editorial analytics pipelines, content operations teams checking ingested data, or any workflow processing up to 200 rows of article-level data (published_articles, word_count) without needing live lookups, predictions, or external integrations. At $0.01 USDC for three reports, it is cost-efficient versus running separate quality and stats tools.
Side effects
- More than 200 rows submitted — API will reject with validation error
- Missing required fields (row_id, channel_group, date, published_articles, word_count) in any row cause rejection
- Invalid date format (must be YYYY-MM-DD) causes schema validation failure
- bins parameter out of range (must be 1–30) causes rejection
- Non-numeric values in published_articles or word_count where numbers expected
- Payment failure or insufficient USDC balance (x402 payment protocol error)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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