{"uid":"cap_9CGQRb8K9ccHLai1QVLdU","slug":"data-freshness-duplicate-key-report-and-numeric-row-ordering-035ab397","name":"Data Freshness Duplicate Key Report and Numeric Row Ordering","description":"Data freshness — Duplicate key report + Numeric row ordering: Duplicate key report + Numeric row ordering 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-06-058?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_4R9aD5Z6skgk8gblNjXon","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":"Generates a duplicate key report and numeric row ordering analysis for up to 200 data freshness records containing age_minutes and record_count fields.","exampleAgentPrompt":"Check these data freshness records for duplicate keys and also give me a numeric ordering by age_minutes — I have 4 rows: row-1 in group-a dated 2026-10-01 with age_minutes 10 and record_count 1, row-2 in group-b dated 2026-10-02 with age_minutes 20 and record_count 2, row-3 in group-a dated 2026-10-03 with age_minutes 15 and record_count 3, and row-4 in group-b dated 2026-10-04 with age_minutes 30 and record_count 4.","exampleUseCases":[{"title":"Pipeline freshness duplicate audit","prompt":"I have a list of 50 data freshness records from my ETL pipeline — each has a row_id, dataset_group, date, age_minutes, and record_count. Can you run a duplicate key report on them and also rank them numerically by age_minutes so I can see which datasets are most stale?"},{"title":"Record count ordering for data monitoring","prompt":"Here are 30 freshness tracking rows from my monitoring system with row IDs, groups, dates, age in minutes, and record counts. Give me a duplicate key report and order them numerically by record_count so I know which groups have the most records."},{"title":"QA check for freshness data ingestion","prompt":"I just ingested a batch of 80 data freshness rows and want to make sure there are no duplicate keys before I process them further — can you run the duplicate key report and also give me a numeric row ordering by age_minutes for those rows?"}],"resultDescription":"Returns two independent analytical reports: (1) a duplicate key report identifying any repeated keys among the supplied row records, and (2) a numeric row ordering ranking the rows by the selected numeric field (age_minutes or record_count). Results are computed locally from the supplied data with no external lookups.","failureModes":["Exceeds 200-row limit — request rejected","Missing required fields (row_id, dataset_group, date, age_minutes, record_count) — validation error","Invalid date format (must be YYYY-MM-DD) — schema validation failure","Invalid field enum value (must be age_minutes or record_count) — rejected","Empty rows array — rejected","Payment not included or insufficient — 402 error"],"whenToPreferThis":"Choose this endpoint when you need both duplicate key detection and numeric ordering on data freshness records (age_minutes, record_count) in a single low-cost call. It is purpose-built for data freshness monitoring data and operates entirely on supplied data with no external dependencies, making it fast, deterministic, and privacy-safe. Ideal for ETL quality checks, pipeline audits, or data freshness dashboards with up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T12:51:28.691Z","isFirstParty":false,"canonicalSlug":"data-freshness-duplicate-key-report-and-numeric-row-ordering-035ab397"}