{"uid":"cap_FiYOrbylUEBls2RFguGuZ","slug":"join-coverage-analytics-exact-row-deduplication-adjacent-row-changes-9a1d843e","name":"Join Coverage Analytics — Exact Row Deduplication + Adjacent Row Changes","description":"Join coverage — Exact row deduplication + Adjacent row changes: Exact row deduplication + Adjacent row changes for supplied join coverage records (matched_rows, source_rows). 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-09-046?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","matched_rows","source_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"matched_rows":{"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","source_rows":1,"matched_rows":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_rows":2,"matched_rows":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["matched_rows","source_rows"],"type":"string","default":"matched_rows"}}},"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_irKWxfPpS8x2Tf5kiGMdq","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":"Runs two local analytical reports on join coverage data: exact row deduplication and adjacent row change detection, for up to 200 supplied rows.","exampleAgentPrompt":"Can you run exact row deduplication and adjacent row change detection on my join coverage data — I have rows with row_id, date, dataset_group, matched_rows, and source_rows fields, and I want to analyze the matched_rows field across up to 50 rows?","exampleUseCases":[{"title":"Deduplicating ETL join coverage logs","prompt":"I have a batch of join coverage records from our ETL pipeline — each row has a row_id, date like 2025-06-01, a dataset_group, and both matched_rows and source_rows counts. Can you run exact row deduplication on the matched_rows field and tell me which records are duplicates?"},{"title":"Spotting day-over-day changes in source rows","prompt":"I want to detect where source_rows values change between adjacent rows in my join coverage dataset — I have about 80 rows with dates running from 2025-01-01 through 2025-03-31, grouped by dataset_group. Can you run the adjacent row changes report on the source_rows field?"},{"title":"Auditing join coverage data before pipeline merge","prompt":"Before we merge this dataset, I need to check for exact duplicate join coverage rows and also flag any adjacent row changes in matched_rows — here are 120 rows with row_id, date, dataset_group, matched_rows, and source_rows. Can you run both reports?"}],"resultDescription":"Returns two analytical reports: (1) an exact row deduplication report identifying repeated records among the supplied join coverage rows, and (2) an adjacent row changes report flagging where the selected field (matched_rows or source_rows) changes between consecutive rows. Both reports are computed locally against the supplied data with no external lookups.","failureModes":["Exceeding 200 rows causes rejection — batch must be split","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors","Invalid date format (non-YYYY-MM-DD) causes schema rejection","Null values in the selected field may affect change detection output","Submitting fewer than 1 row returns an error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, self-contained deduplication and sequential change analysis on join coverage records without any external data lookups. It is ideal for data quality audits during ETL pipelines, pre-merge validation, or routine join coverage monitoring where you already have the raw rows and need two complementary analytical views at low cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-11T12:48:35.309Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-exact-row-deduplication-adjacent-row-changes-9a1d843e"}