{"uid":"cap_2JWwr6NLJ9a6kGDhZ8xM9","slug":"data-freshness-numeric-row-ordering-iqr-outlier-flags-68655240","name":"Data Freshness — Numeric Row Ordering & IQR Outlier Flags","description":"Data freshness — Numeric row ordering + IQR outlier flags: Numeric row ordering + IQR outlier flags for supplied data freshness records (age_minutes, record_count). 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-06-119?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","age_minutes","record_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"age_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"record_count":{"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","age_minutes":10,"record_count":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","age_minutes":20,"record_count":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","age_minutes":15,"record_count":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","age_minutes":30,"record_count":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["age_minutes","record_count"],"type":"string","default":"age_minutes"}}},"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_nKVCFhpXXk51m2OxvTpvD","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":"Ranks rows by age_minutes or record_count and flags IQR-based outliers in supplied data freshness records, producing two analytical reports per call.","exampleAgentPrompt":"Can you rank these data freshness records by age_minutes and flag any IQR outliers? I have 4 rows: row-1 (group-a, 2026-10-01, age=10, count=1), row-2 (group-b, 2026-10-02, age=20, count=2), row-3 (group-a, 2026-10-03, age=15, count=3), row-4 (group-b, 2026-10-04, age=30, count=4) — give me both the ordering report and the outlier flags for age_minutes.","exampleUseCases":[{"title":"Pipeline freshness anomaly detection","prompt":"I have 50 data pipeline records with age_minutes and record_count — can you rank them by age_minutes and tell me which ones are IQR outliers so I can investigate stale feeds?"},{"title":"Dataset group outlier review","prompt":"Here are 30 freshness monitoring rows across two dataset groups. Rank them by record_count and flag any that fall outside the IQR bounds — I need both reports."},{"title":"Data quality audit for ingestion jobs","prompt":"I'm auditing ingestion job freshness. Can you take these 80 rows with age_minutes and record_count values, order them by age_minutes, and highlight which rows are statistical outliers using IQR?"}],"resultDescription":"Returns two analytical reports: (1) rows ordered/ranked by the selected numeric field (age_minutes or record_count), and (2) IQR-based outlier flags identifying which rows fall below Q1-1.5×IQR or above Q3+1.5×IQR. No external lookups or predictions are made — analysis is purely local and deterministic based on the supplied data.","failureModes":["Input array is empty (minItems:1 violated) — validation error","More than 200 rows submitted — request rejected","Missing required fields (row_id, date, dataset_group, age_minutes, record_count) — validation error","Invalid date format (must match YYYY-MM-DD) — schema validation failure","Field enum value not 'age_minutes' or 'record_count' — rejected","All values null for selected field — IQR computation may be undefined","Payment not attached or insufficient (requires 0.01 USDC via x402) — 402 response"],"whenToPreferThis":"Choose this endpoint when you have up to 200 data freshness records with age_minutes and/or record_count fields and need both a ranked ordering and IQR-based outlier detection in a single low-cost call ($0.01 USDC). It is ideal for local, deterministic statistical analysis without any external data lookups, predictions, or side effects. Prefer this over generic analytics services when your domain is specifically data pipeline/freshness monitoring and you want two reports (ordering + outlier flags) in one request.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T07:01:50.874Z","isFirstParty":false,"canonicalSlug":"data-freshness-numeric-row-ordering-iqr-outlier-flags-68655240"}