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Pipeline Durations — String Normalisation + Adjacent Row Changes
x402
Pipeline Durations — String Normalisation + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Runs two local analytical reports on pipeline duration records: string normalisation and adjacent row change detection, for up to 200 rows of run_seconds or processed_rows data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Pipeline durations — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied pipeline durations records (run_seconds, processed_rows). 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 independent analytical reports: (1) a string normalisation report standardising the selected numeric field (run_seconds or processed_rows) across supplied rows, and (2) an adjacent row changes report identifying value differences between consecutive rows, all computed locally without external lookups.
Example use cases
Detect pipeline slowdowns between runs
“I have a week of daily pipeline run records with run_seconds logged per dataset group — can you check for adjacent row changes so I can spot where durations jumped between consecutive days? Here are my 10 rows with row IDs, dates, dataset groups, and run_seconds values.”
Normalise processed row counts across groups
“Can you run string normalisation on my processed_rows data across these 50 pipeline records? I want to standardise the values so I can compare group-a and group-b output volumes meaningfully — I'll send you the full rows with row_id, date, dataset_group, and processed_rows.”
Audit ETL batch duration consistency
“I want two reports on my ETL pipeline logs: string normalisation and adjacent row changes for the run_seconds field. I have about 150 rows covering last quarter, each with a date, row_id, dataset_group, and run_seconds — can you run both analyses at once?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-05-029?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two complementary analytical passes — string normalisation and sequential row change detection — on pipeline duration data (run_seconds or processed_rows) in a single call. It is ideal for ETL monitoring, data quality audits, or pipeline performance reviews where you want both a normalised view and a row-to-row delta report without any external API calls or live predictions.
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, date, run_seconds, processed_rows) on any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Field selector not one of 'run_seconds' or 'processed_rows' — enum validation error
- Numeric values outside allowed range (-1e12 to 1e12) — schema validation error
- Empty rows array — minimum items constraint violated
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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