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News Archive Completeness — String Normalisation + Daily Sum Series
x402
News Archive Completeness — String Normalisation + Daily Sum Series 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 string normalisation and daily sum series analysis on up to 200 news archive completeness records (indexed_items, expected_items), returning two analytical reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
News archive completeness — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied news archive completeness records (indexed_items, expected_items). 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 analytical reports: (1) a string normalisation report for the selected field across all supplied rows, and (2) a daily sum series aggregating the chosen numeric field (indexed_items or expected_items) by date — all computed locally from supplied data, with no external lookups or predictions.
Example use cases
Daily indexing gap trend analysis
“I've got 90 days of news archive records across three channel groups — 'breaking-news', 'sports', and 'entertainment' — with indexed_items and expected_items per day. Can you compute a daily sum series on indexed_items so I can see how total indexing volume trends over time?”
Channel group label normalisation
“My news archive completeness dataset has messy channel_group strings like 'Sports ', 'SPORTS', and 'sports' across 120 rows. Can you run string normalisation on those labels so I can group them consistently, alongside a daily sum on expected_items?”
Expected vs indexed coverage audit
“Here are 200 rows of daily archive records for our news crawler — each has a date, a channel group, an indexed count, and an expected count. Run the string normalisation and daily sum series on expected_items so I can audit where our coverage is falling short.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-23-027?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and daily sum series analysis on news archive completeness data in a single low-cost call, without requiring any external data sources, live lookups, or predictions. Ideal for pipelines that batch-process up to 200 archive records and need reproducible, locally-computed analytics on indexed vs expected item counts across channel groups.
Side effects
- Rows array empty or missing — validation error returned
- More than 200 rows submitted — request rejected or truncated
- Invalid date format (not YYYY-MM-DD) — row rejected or error
- Null values in indexed_items/expected_items — may affect sum series output
- Invalid field enum value (not 'indexed_items' or 'expected_items') — error response
- Missing required fields (row_id, channel_group, date) — schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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