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Pipeline Durations Analytics — Record Quality Audit, String Normalisation & Category Frequencies
x402
Pipeline Durations Analytics — Record Quality Audit, String Normalisation & Category Frequencies is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Runs three local analytical reports on pipeline duration records: record quality audit, string normalisation, and category frequency analysis for up to 200 rows of run_seconds and processed_rows data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Pipeline durations — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies for supplied pipeline durations records (run_seconds, processed_rows). 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 for the submitted pipeline duration rows: (1) a record quality audit flagging nulls, out-of-range values, and malformed fields; (2) a string normalisation report cleaning dataset_group and date strings; (3) a category frequency table showing how often each dataset_group appears. All computed locally with no external lookups.
Example use cases
ETL pipeline health check
“I have a week's worth of pipeline run logs with run_seconds and processed_rows for two dataset groups — can you audit the record quality, normalise the group names, and tell me how frequently each group appears? Here are 8 rows with dates from 2026-10-01 to 2026-10-08.”
Data quality gate before warehouse load
“Before I load these 50 pipeline duration records into our data warehouse, can you run a quality audit on them and flag any malformed strings or missing values in the dataset_group or date fields?”
Category frequency summary for pipeline reporting
“I need to know how often each dataset_group shows up across my 120 pipeline duration records from last month — can you compute category frequencies and normalise any inconsistent group name strings?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-05-195?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined data quality audit, string normalisation, and category frequency analysis for pipeline duration records (run_seconds, processed_rows) in a single cheap call. It is purpose-built for ETL/pipeline log data with up to 200 rows and delivers three reports at once for $0.01 USDC, making it ideal for lightweight, local analytical profiling without any external data lookups or predictions.
Side effects
- Rows array empty or missing — validation error
- More than 200 rows submitted — rejected with max-items error
- run_seconds or processed_rows outside allowed numeric range — schema rejection
- date field not matching YYYY-MM-DD pattern — schema rejection
- row_id missing or empty — validation error
- Payment not provided or insufficient — x402 payment required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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