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Pipeline Durations — Record Quality Audit, String Normalisation & Missing-Value Fill
x402
Pipeline Durations — Record Quality Audit, String Normalisation & Missing-Value Fill 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 data-quality reports (record audit, string normalisation, missing-value fill) on pipeline duration records containing run_seconds and processed_rows fields, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Pipeline durations — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill 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 supplied pipeline duration rows: (1) a record quality audit identifying malformed or invalid records, (2) a string normalisation report flagging and correcting inconsistent string values in fields like dataset_group, and (3) a missing-value fill report showing where run_seconds or processed_rows were null and what values were substituted using the chosen method (zero, mean, or median). All reports are computed locally with no external lookups.
Example use cases
Pre-load ETL pipeline data audit
“Before I load my pipeline run logs to the warehouse, can you audit the record quality, normalise any string fields, and fill any missing run_seconds values using the median — here are my 50 rows with row IDs, dataset groups, dates, run_seconds, and processed_rows?”
Missing processed_rows detection and fill
“I've got 120 rows of pipeline duration records and some of the processed_rows values are missing — can you run the three quality reports and fill those gaps using the mean method?”
String normalisation check for pipeline metrics
“Can you check my pipeline metrics dataset for string formatting issues, audit record quality, and fill any null values in run_seconds with zero? I'll send you 30 rows covering October runs across group-a and group-b.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-05-208?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined, low-cost ($0.01 USDC) batch data-quality pass — record audit, string normalisation, and missing-value fill — on pipeline duration data (run_seconds, processed_rows) in a single call, without needing external lookups, predictions, or professional assessments. It is ideal for pre-ingestion validation of ETL run logs for up to 200 rows.
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, run_seconds, processed_rows, dataset_group) causes row-level rejection
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- Selecting an unsupported fill method (not zero/mean/median) returns an enum validation error
- Submitting zero rows returns a minItems validation error
- Numeric values outside the allowed range (±1,000,000,000,000) are rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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