{"uid":"cap_fZ4VCoyI6SbdQx6BGPaka","slug":"pipeline-durations-analytics-quality-audit-deduplication-and-base-100-739957ec","name":"Pipeline Durations Analytics: Quality Audit, Deduplication, and Base-100 Series","description":"Pipeline durations — Record quality audit + Exact row deduplication + Base-100 series: Record quality audit + Exact row deduplication + Base-100 series 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-05-218?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_mjO2lzlg-HjHCcu2GKXgk","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 three independent analytical reports on pipeline duration records: record quality audit, exact row deduplication, and base-100 indexed series — all locally, without external lookups.","exampleAgentPrompt":"Can you run a quality audit, exact deduplication check, and base-100 series on my pipeline duration records? I have rows with run_seconds and processed_rows fields — use run_seconds as the field and base the index at position 0.","exampleUseCases":[{"title":"ETL pipeline run quality check","prompt":"I've got a batch of 50 pipeline execution records with run_seconds and processed_rows — can you audit them for data quality issues, deduplicate any identical rows, and generate a base-100 index series on run_seconds starting from position 0?"},{"title":"Duplicate pipeline log detection","prompt":"Here are my pipeline logs from the last month — each has a row_id, date, dataset_group, run_seconds, and processed_rows. Can you find any exact duplicate rows and also give me a quality audit of the whole set?"},{"title":"Normalize pipeline durations for comparison","prompt":"I want to compare pipeline run times across dataset groups in a normalized way — can you take these records and produce a base-100 indexed series on run_seconds anchored at row index 0, plus flag any quality issues in the data?"}],"resultDescription":"Returns three independent reports: (1) a record quality audit flagging missing, invalid, or out-of-range values in the supplied rows; (2) an exact row deduplication report identifying and removing duplicate records; and (3) a base-100 indexed series for the selected numeric field (run_seconds or processed_rows), normalized relative to a specified base row index. All processing is done locally on the supplied data with no external lookups.","failureModes":["Empty or missing rows array returns a validation error","More than 200 rows submitted exceeds the row limit and is rejected","Invalid date format (not YYYY-MM-DD) causes row-level validation failure","base_index value out of bounds for supplied row count causes indexing error","Non-numeric values in run_seconds or processed_rows may be flagged or rejected","Missing required fields (row_id, dataset_group, date) cause schema validation errors"],"whenToPreferThis":"Choose this endpoint when you need to simultaneously validate data quality, remove duplicates, and produce a normalized index series from pipeline duration records in a single low-cost call. Ideal for ETL monitoring, pipeline observability, and data hygiene workflows where you have up to 200 rows of run_seconds or processed_rows data and want three complementary analytical views without any external data lookups or live predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T06:54:28.269Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-analytics-quality-audit-deduplication-and-base-100-739957ec"}