{"uid":"cap_dpcG6LI4ZoUmeFkQGOfFg","slug":"pipeline-durations-record-quality-audit-numeric-interval-filter-fbafbb10","name":"Pipeline Durations — Record Quality Audit + Numeric Interval Filter","description":"Pipeline durations — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-05-008?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","run_seconds","processed_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"run_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","run_seconds":10,"dataset_group":"group-a","processed_rows":1},{"date":"2026-10-02","row_id":"row-2","run_seconds":20,"dataset_group":"group-b","processed_rows":2},{"date":"2026-10-03","row_id":"row-3","run_seconds":15,"dataset_group":"group-a","processed_rows":3},{"date":"2026-10-04","row_id":"row-4","run_seconds":30,"dataset_group":"group-b","processed_rows":4}],"maxItems":200,"minItems":1},"field":{"enum":["run_seconds","processed_rows"],"type":"string","default":"run_seconds"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_KRkvDWl7n2_4iopztjz-8","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs a record quality audit and numeric interval filter on pipeline duration records (run_seconds, processed_rows), returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you audit these 50 pipeline duration records for data quality issues and also filter them to find any rows where run_seconds falls outside the range 0 to 500? The records have fields: row_id, dataset_group, date, run_seconds, and processed_rows.","exampleUseCases":[{"title":"ETL pipeline health check","prompt":"I have a list of 120 pipeline run records with run_seconds and processed_rows values — can you audit them for missing or invalid data and flag any rows where run_seconds is outside 10 to 3600 seconds?"},{"title":"Detecting anomalously fast pipeline runs","prompt":"These are my daily pipeline duration logs for the last month. Run a quality audit and filter out any records where processed_rows is below 1 or above 500000 so I can investigate them."},{"title":"Pre-ingestion data validation","prompt":"Before I load these pipeline records into our data warehouse, can you check them for quality issues and identify any rows where run_seconds exceeds 86400 — I want to catch any obviously bad durations before they pollute the dataset?"}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit identifying issues such as nulls, invalid values, or anomalies in the pipeline duration records; and (2) a numeric interval filter report listing rows where the selected field (run_seconds or processed_rows) falls outside the specified minimum/maximum range. Covers up to 200 input rows per call.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, date, run_seconds, processed_rows, dataset_group) cause row-level validation errors","Invalid date format (not YYYY-MM-DD) may cause parsing failures","Minimum value greater than maximum value may produce empty or nonsensical interval filter results","Non-numeric values in run_seconds or processed_rows when nulls are not expected"],"whenToPreferThis":"Choose this endpoint when you have pipeline execution records with run_seconds and/or processed_rows fields and need both a general data quality audit and a numeric range filter in a single low-cost call. Ideal for pre-ingestion validation, anomaly screening, or routine ETL monitoring on small-to-medium batches (up to 200 rows). Not suitable for real-time streaming, large-scale datasets, or external data lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T06:54:48.396Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-record-quality-audit-numeric-interval-filter-fbafbb10"}