{"uid":"cap_A5MvSE7NHjrV9N35FDkb1","slug":"validation-rule-results-numeric-interval-filter-iqr-outlier-flags-1f01e5bf","name":"Validation Rule Results — Numeric Interval Filter + IQR Outlier Flags","description":"Validation rule results — Numeric interval filter + IQR outlier flags: Numeric interval filter + 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-08-130?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"},"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_RywNOaMZWqb0-cLjDDTgq","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":"Applies a numeric interval filter and IQR-based outlier detection to supplied validation rule results records (passed_rules, total_rules), returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have 50 rows of validation rule results with passed_rules and total_rules values — can you run an interval filter keeping only rows where passed_rules is between 10 and 100, and also flag any IQR outliers in the passed_rules column?","exampleUseCases":[{"title":"Flagging anomalous rule pass rates","prompt":"I've got daily validation rule results across two dataset groups for the past month. Can you flag any rows where passed_rules looks like an IQR outlier, and also filter to only rows where passed_rules falls between 5 and 95?"},{"title":"Quality audit on total_rules counts","prompt":"Here are 120 rows of validation pipeline records. Run the interval filter on total_rules between 1 and 500, and also give me IQR outlier flags on total_rules so I can spot any suspiciously extreme rule counts."},{"title":"Detecting irregular validation results by group","prompt":"I want to analyze passed_rules across my dataset groups — filter rows to the 0–50 range and also flag any IQR outliers. I'll upload up to 150 rows for you to process."}],"resultDescription":"Two analytical reports for up to 200 supplied rows: (1) a numeric interval filter report showing which rows fall within the specified minimum–maximum range for the chosen field, and (2) an IQR outlier flag report identifying rows whose field values are statistical outliers based on interquartile range. Both reports are computed locally with no external data lookup.","failureModes":["Exceeding 200 rows returns an error or truncated results","Missing required fields (row_id, dataset_group, date, passed_rules, total_rules) cause validation failures","Invalid date format (not YYYY-MM-DD) triggers a schema error","Minimum greater than maximum may produce empty interval filter results","Null numeric values may affect IQR calculation accuracy"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of validation rule result records and need both a bounded interval filter and IQR-based outlier detection on passed_rules or total_rules in a single API call. It is ideal for lightweight, local statistical analysis of data quality metrics without requiring an external analytics platform. Prefer it over general-purpose analytics services when cost sensitivity matters ($0.01 USDC for two reports) and the dataset fits within the 200-row limit.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T12:51:10.834Z","isFirstParty":false,"canonicalSlug":"validation-rule-results-numeric-interval-filter-iqr-outlier-flags-1f01e5bf"}