{"uid":"cap_ZwnRZq3DaAjYi-XssOncv","slug":"validation-rule-results-exact-row-deduplication-iqr-outlier-flags-df2b9a72","name":"Validation Rule Results — Exact Row Deduplication + IQR Outlier Flags","description":"Validation rule results — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags for supplied validation rule results records (passed_rules, total_rules). 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-08-049?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","passed_rules","total_rules"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_rules":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"passed_rules":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_rules":1,"passed_rules":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","total_rules":2,"passed_rules":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","total_rules":3,"passed_rules":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","total_rules":4,"passed_rules":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["passed_rules","total_rules"],"type":"string","default":"passed_rules"}}},"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_WorWLKITU-gF2TEcT8X1V","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":"Deduplicates exact duplicate rows and flags IQR-based outliers in validation rule result records (passed_rules, total_rules) for up to 200 rows.","exampleAgentPrompt":"Can you deduplicate these validation rule result records and flag any IQR outliers in the passed_rules field? I have about 50 rows with row_id, dataset_group, date, passed_rules, and total_rules — I need both reports.","exampleUseCases":[{"title":"Data quality pipeline deduplication check","prompt":"I have 120 rows of validation rule results from my data pipeline — each row has a row_id, dataset_group, date, passed_rules, and total_rules. Can you deduplicate them exactly and flag any IQR outliers in passed_rules so I can clean this up before ingesting?"},{"title":"Outlier detection in rule compliance data","prompt":"My validation monitoring dataset has some suspicious entries in total_rules. Can you run IQR outlier detection on the total_rules field across my 80 validation rule result records and also remove any exact duplicate rows?"},{"title":"Audit validation results across dataset groups","prompt":"We track passed_rules and total_rules across multiple dataset groups daily. Can you take these 150 validation result records and give me a deduplication report plus IQR-based outlier flags on passed_rules so I can audit which groups have anomalies?"}],"resultDescription":"Two independent analytical reports: (1) an exact row deduplication report identifying and removing fully duplicate rows from the input, and (2) an IQR-based outlier detection report flagging rows where the selected numeric field (passed_rules or total_rules) falls outside the interquartile range bounds. Both reports are computed locally with no external lookups.","failureModes":["Input exceeds 200 rows — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, passed_rules, total_rules) cause validation errors","Numeric fields outside allowed range (-1e12 to 1e12) will fail schema validation","Date strings not matching YYYY-MM-DD pattern will be rejected","Too few rows to compute meaningful IQR statistics (e.g. fewer than 4 rows) may produce degenerate outlier results","Invalid field enum value (must be 'passed_rules' or 'total_rules') will cause an error"],"whenToPreferThis":"Choose this endpoint when you need both exact duplicate removal and IQR-based statistical outlier flagging on validation rule result data (passed_rules, total_rules) in a single inexpensive call. It is ideal for data quality pipelines where you want to clean records before downstream analysis without needing external data sources, ML predictions, or professional assessments. Best for small-to-medium datasets up to 200 rows processed locally and cheaply.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-11T12:48:23.672Z","isFirstParty":false,"canonicalSlug":"validation-rule-results-exact-row-deduplication-iqr-outlier-flags-df2b9a72"}