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Discussion Response — String Normalisation + Daily Sum Series
x402
Discussion Response — 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 2026-10-30).
Runs two local analytical reports on discussion response data: string normalisation of categorical fields and a daily sum time series for response_count or response_minutes (up to 200 rows).
Price / call$0.01
Success—
StatusUnknown
How this service works
Discussion response — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied discussion response records (response_count, response_minutes). 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
Returns two analytical reports for the supplied rows: (1) a string normalisation report on the categorical/text fields (such as channel_group), and (2) a daily sum time series for the chosen numeric field (response_count or response_minutes), aggregated by date. Results are computed locally with no external lookups.
Example use cases
Daily engagement totals for forum channels
“I have a week of discussion response data across two channel groups — can you normalise the channel_group strings and compute a daily sum series for response_count? Here are the rows: row-1, 2026-10-01, group-a, 10 responses, 1 minute; row-2, 2026-10-02, group-b, 20 responses, 2 minutes; row-3, 2026-10-03, group-a, 15 responses, 3 minutes.”
Time-on-thread aggregation by day
“Can you take these discussion response records and produce a daily sum series for response_minutes? I need to see total minutes spent per day: row-1 on 2026-10-01 group-a 10 responses 5 minutes, row-2 on 2026-10-02 group-b 25 responses 12 minutes, row-3 on 2026-10-03 group-a 8 responses 3 minutes. Also normalise the string fields.”
Channel label cleanup before reporting
“My discussion data has inconsistent channel_group labels — please run string normalisation on them and also give me the daily sum series for response_count. Data: row-1, 2026-11-01, Group A, 50 responses, 10 minutes; row-2, 2026-11-01, group-a, 30 responses, 6 minutes; row-3, 2026-11-02, GROUP-B, 40 responses, 8 minutes.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-07-027?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation of categorical labels and a daily sum time series computed together in a single call against your own supplied discussion response data, without any external data lookup or prediction. It is ideal for lightweight, self-contained analytical preprocessing of up to 200 discussion response records at very low cost ($0.01 USDC for both reports).
Side effects
- Empty or missing rows array returns a validation error
- rows array exceeding 200 items is rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Null or out-of-range numeric values (beyond ±1,000,000,000,000) may cause computation errors
- Missing required fields (row_id, channel_group, date, response_count, response_minutes) on any row returns an error
- Invalid field enum value (not response_count or response_minutes) is rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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