{"uid":"cap_TYJ5Mk0pI0CD_11i-2SVg","slug":"schema-conformity-numeric-row-ordering-iqr-outlier-flags-928f4c29","name":"Schema Conformity — Numeric Row Ordering + IQR Outlier Flags","description":"Schema conformity — Numeric row ordering + IQR outlier flags: Numeric row ordering + 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-02-119?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_5nzw9Zk-xjWKqXhUdZFAQ","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":"Sorts schema conformity records by numeric value and flags IQR-based outliers across valid_records and checked_records fields for up to 200 rows.","exampleAgentPrompt":"Rank my schema conformity rows by valid_records and flag any IQR outliers — here are 4 rows: row-1 group-a 2026-10-01 valid_records=10 checked_records=1, row-2 group-b 2026-10-02 valid_records=20 checked_records=2, row-3 group-a 2026-10-03 valid_records=15 checked_records=3, row-4 group-b 2026-10-04 valid_records=30 checked_records=4, and use valid_records as the target field.","exampleUseCases":[{"title":"Daily data quality audit","prompt":"I have 50 rows of daily schema conformity checks — can you sort them by valid_records and flag any statistical outliers using IQR? Here's the data with row IDs, dataset groups, dates, and both valid_records and checked_records values."},{"title":"Detecting anomalous checked_records spikes","prompt":"Run an IQR outlier analysis on my checked_records field across these 30 conformity records — I want to see which rows are statistically unusual and how the rows rank numerically."},{"title":"Multi-group conformity ranking","prompt":"I have schema conformity data across two dataset groups over the past month — can you order all 80 rows by their valid_records value and tell me which ones fall outside the IQR range so I can investigate?"}],"resultDescription":"Returns two analytical reports: (1) rows ordered numerically by the selected field (valid_records or checked_records), and (2) IQR-based outlier flags indicating which rows fall below Q1−1.5×IQR or above Q3+1.5×IQR. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — endpoint rejects with error","Missing required fields (row_id, date, valid_records, checked_records) cause validation failure","Invalid date format (non-YYYY-MM-DD) triggers pattern validation error","All null values in selected field produce no meaningful IQR computation","Empty rows array rejected due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you need both numeric ordering and IQR-based outlier detection on schema conformity metrics (valid_records, checked_records) in a single low-cost call. Ideal for data quality pipelines processing up to 200 rows where no live data lookup or ML prediction is needed — purely analytical, deterministic, and runs locally on submitted data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:41:13.613Z","isFirstParty":false,"canonicalSlug":"schema-conformity-numeric-row-ordering-iqr-outlier-flags-928f4c29"}