{"uid":"cap_MWi7AK64eFw9dUyOf-Xuw","slug":"pipeline-durations-record-quality-audit-string-normalisation-iqr-9a45dbe7","name":"Pipeline Durations — Record Quality Audit + String Normalisation + IQR Outlier Flags","description":"Pipeline durations — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags 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-05-203?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"}}},"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_xg5WouOLwZ7vQYTyjLK3s","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 analytical reports on supplied pipeline duration records: a record quality audit, string normalisation, and IQR-based outlier flagging for run_seconds or processed_rows fields.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and IQR outlier check on my pipeline duration records? I have up to 50 rows with fields like run_seconds and processed_rows — flag any outliers and quality issues in the run_seconds field.","exampleUseCases":[{"title":"Outlier detection in ETL run times","prompt":"I have a batch of 80 pipeline run records with run_seconds and processed_rows values — can you flag any statistical outliers in run_seconds using IQR and tell me which rows look suspicious?"},{"title":"Quality audit for pipeline log data","prompt":"Can you audit the quality of these 120 pipeline duration records for me? I want to know which rows have missing values, format issues, or anomalies in the processed_rows field."},{"title":"Normalise dataset group labels in pipeline logs","prompt":"My pipeline logs have messy dataset_group strings across 60 rows — can you normalise them and give me a clean string normalisation report along with any IQR outlier flags for run_seconds?"}],"resultDescription":"Returns three independent analytical reports for the supplied rows: (1) a record quality audit identifying missing, malformed, or invalid values; (2) string normalisation results for text fields like dataset_group; and (3) IQR-based outlier flags identifying statistically anomalous values in the chosen numeric field (run_seconds or processed_rows). Up to 200 rows per call.","failureModes":["More than 200 rows submitted — request rejected","Missing required fields (row_id, date, run_seconds, processed_rows) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Invalid field selector (not run_seconds or processed_rows) — enum error","Empty rows array — rejected with minItems violation"],"whenToPreferThis":"Choose this endpoint when you need a fast, offline, multi-report analytical pass over pipeline duration records without external lookups or predictions. Ideal for data engineering teams who want quality auditing, string normalisation, and statistical outlier detection (IQR method) bundled in a single cheap call for batches up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:23.403Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-record-quality-audit-string-normalisation-iqr-9a45dbe7"}