{"uid":"cap_7hmp-PtfVTg8RESLD34sl","slug":"schema-conformity-grouped-numeric-summary-with-iqr-outlier-flags-ff9f0924","name":"Schema Conformity Grouped Numeric Summary with IQR Outlier Flags","description":"Schema conformity — Grouped numeric summary + IQR outlier flags: Grouped numeric summary + IQR outlier flags for supplied schema conformity records (valid_records, checked_records). 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-02-094?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","valid_records","checked_records"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"valid_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","valid_records":10,"checked_records":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","valid_records":20,"checked_records":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","valid_records":15,"checked_records":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","valid_records":30,"checked_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["valid_records","checked_records"],"type":"string","default":"valid_records"}}},"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_PJFiphxKOv9BtucY7BhYl","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":"Computes grouped descriptive statistics and IQR-based outlier flags for schema conformity records (valid_records and checked_records) across up to 200 rows in two independent reports.","exampleAgentPrompt":"Can you run a grouped numeric summary and IQR outlier analysis on my schema conformity data — I have up to 50 rows with dataset_group, date, valid_records, and checked_records columns, and I want two reports focusing on the valid_records field?","exampleUseCases":[{"title":"Data quality audit outlier detection","prompt":"I have 80 rows of schema conformity records across three dataset groups with valid_records and checked_records counts per day — can you summarize them by group and flag any IQR outliers in the valid_records field?"},{"title":"Monitoring checked_records anomalies","prompt":"Run a grouped summary and IQR outlier check on my checked_records data — I've got about 120 conformity rows spanning multiple dataset groups and dates, and I need to know which rows look anomalous."},{"title":"Comparing conformity across dataset groups","prompt":"I want to understand how valid_records vary across my different dataset groups — can you give me grouped descriptive stats and highlight any outliers using IQR for these 60 schema conformity records?"}],"resultDescription":"Returns two independent analytical reports per call: (1) a grouped numeric summary with descriptive statistics (e.g. mean, median, min, max, count) broken down by dataset_group, and (2) IQR-based outlier flags identifying rows whose values fall outside the interquartile range, for the selected field (valid_records or checked_records) across up to 200 input rows.","failureModes":["Input array exceeds 200 rows — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, valid_records, checked_records) cause validation errors","Invalid date format (must match YYYY-MM-DD pattern) triggers schema rejection","Null values in valid_records or checked_records may affect IQR computation accuracy","Single-row or single-group datasets may produce degenerate or uninformative IQR results"],"whenToPreferThis":"Choose this endpoint when you have tabular schema conformity data with valid_records and checked_records columns and need both grouped descriptive statistics and IQR-based outlier detection in a single low-cost call. It is ideal for data quality monitoring workflows where you want offline, local analytical computation without external lookups or predictions. Best suited for batches of up to 200 rows where two simultaneous analytical reports are needed cheaply at $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T00:47:14.568Z","isFirstParty":false,"canonicalSlug":"schema-conformity-grouped-numeric-summary-with-iqr-outlier-flags-ff9f0924"}