{"uid":"cap_8JXulm2be1QMsi2_fUXL1","slug":"join-coverage-analytics-numeric-row-ordering-adjacent-row-changes-4565750d","name":"Join Coverage Analytics — Numeric Row Ordering & Adjacent Row Changes","description":"Join coverage — Numeric row ordering + Adjacent row changes: Numeric row ordering + 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-09-116?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_va0KTJftQJj1KjTCTbHpf","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":"Analyzes join coverage data (matched_rows, source_rows) by computing numeric row ordering and detecting adjacent row changes across up to 200 rows in two independent analytical reports.","exampleAgentPrompt":"Can you run numeric row ordering and adjacent row change analysis on my join coverage data? I have 4 rows: 2026-10-01 row-1 group-a source_rows=1 matched_rows=10, 2026-10-02 row-2 group-b source_rows=2 matched_rows=20, 2026-10-03 row-3 group-a source_rows=3 matched_rows=15, 2026-10-04 row-4 group-b source_rows=4 matched_rows=30 — analyze the matched_rows field.","exampleUseCases":[{"title":"Pipeline join quality trend review","prompt":"I need to check how my pipeline's matched_rows have been changing day over day — can you run numeric ordering and adjacent row change detection on these 5 records from last week, grouped by dataset_group, analyzing the matched_rows field?"},{"title":"Source row anomaly detection across groups","prompt":"Can you analyze these 10 join coverage records for adjacent row changes in source_rows? I want to see if there are any sudden jumps or drops between consecutive rows across my group-a and group-b datasets."},{"title":"ETL coverage audit for data team","prompt":"Our ETL team needs a quick audit of join coverage — please run numeric row ordering and adjacent change analysis on these 8 date-stamped records with matched_rows values, so we can spot where coverage dropped unexpectedly."}],"resultDescription":"Returns two independent analytical reports for the supplied join coverage rows: (1) a numeric row ordering report ranking rows by the selected field (matched_rows or source_rows), and (2) an adjacent row changes report showing value differences between consecutive rows. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row or more than 200 rows submitted — request rejected","Invalid date format (not YYYY-MM-DD) causes validation error","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) per row","Field selector not one of 'matched_rows' or 'source_rows' — enum validation failure","Numeric values outside allowed range (±1,000,000,000,000) rejected"],"whenToPreferThis":"Choose this endpoint when you need fast, local analytical computation on join coverage data specifically combining numeric row ordering with adjacent row change detection in a single call. Ideal for data engineering and ETL teams auditing pipeline join coverage without needing external data enrichment, predictions, or live lookups. Best when you have up to 200 date-stamped coverage records across dataset groups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T06:44:42.551Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-numeric-row-ordering-adjacent-row-changes-4565750d"}