{"uid":"cap_C_UzDwXzrKGMSIX4HRpV3","slug":"data-freshness-analytics-exact-row-deduplication-grouped-numeric-6f2dac99","name":"Data Freshness Analytics — Exact Row Deduplication + Grouped Numeric Summary","description":"Data freshness — Exact row deduplication + Grouped numeric summary: Exact row deduplication + Grouped numeric summary 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-06-040?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_oWcmOMcVD6gfOPIAOQLsA","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":"Deduplicates exact rows and computes grouped numeric summaries for data freshness records containing age_minutes and record_count fields.","exampleAgentPrompt":"I have a list of data freshness records with age_minutes and record_count fields across groups like 'group-a' and 'group-b' — can you deduplicate the exact rows and then give me a grouped numeric summary for the age_minutes field?","exampleUseCases":[{"title":"Auditing freshness lag across pipeline datasets","prompt":"I've got up to 150 data freshness rows from our pipeline, each with a dataset_group and age_minutes — please deduplicate any exact duplicates and summarize the age_minutes stats grouped by dataset_group so I can see which groups are lagging."},{"title":"Cleaning duplicate monitoring records before reporting","prompt":"Our monitoring system sometimes emits duplicate rows. Can you run exact row dedup on these data freshness records and also give me a grouped summary of record_count by dataset_group so I know what's left after cleaning?"},{"title":"Comparing record_count distribution across data groups","prompt":"I want to understand how record_count varies across different dataset groups — please deduplicate these freshness records first and then give me a grouped numeric summary using the record_count field."}],"resultDescription":"Returns two analytical reports: (1) an exact row deduplication report identifying and removing fully duplicate rows from the submitted data freshness records, and (2) a grouped numeric summary (e.g. count, min, max, mean) of the selected field (age_minutes or record_count) broken down by dataset_group. Both reports are computed locally without external lookups.","failureModes":["Exceeding 200 row limit returns a validation error","Missing required fields (row_id, dataset_group, date, age_minutes, record_count) causes rejection","Invalid date format (non YYYY-MM-DD) fails schema validation","Empty rows array rejected (minItems: 1)","Invalid field enum value (must be age_minutes or record_count) causes error","Null numeric values are accepted but may affect summary statistics"],"whenToPreferThis":"Choose this endpoint when you need both exact row deduplication and grouped numeric aggregation on data freshness records (age_minutes, record_count) in a single low-cost call. Ideal for pipelines that need to clean duplicate monitoring logs and immediately summarize freshness metrics by group. Best suited for datasets up to 200 rows where no external data lookup or prediction is needed — pure local analytical computation.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:38:28.731Z","isFirstParty":false,"canonicalSlug":"data-freshness-analytics-exact-row-deduplication-grouped-numeric-6f2dac99"}