{"uid":"cap_2L87jDc6BQVb2tNCZ1vBq","slug":"join-coverage-analytics-daily-sum-series-adjacent-row-changes-c2eaf780","name":"Join Coverage Analytics — Daily Sum Series + Adjacent Row Changes","description":"Join coverage — Daily sum series + Adjacent row changes: Daily sum series + 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-09-137?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_6oONbQVkmjW-vsNG1dbaG","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":"Computes two analytical reports (daily sum series and adjacent row changes) over supplied join coverage data (matched_rows and source_rows) for up to 200 rows.","exampleAgentPrompt":"I have a list of daily join coverage records with matched_rows and source_rows for two dataset groups — can you run the daily sum series and adjacent row changes reports on the matched_rows field for these rows: 2026-10-01 group-a matched=10 source=1, 2026-10-02 group-b matched=20 source=2, 2026-10-03 group-a matched=15 source=3?","exampleUseCases":[{"title":"Daily join match rate trending","prompt":"I have 30 days of join coverage data across two dataset groups with matched_rows and source_rows per day — run the daily sum series report on matched_rows so I can see total match volume by day."},{"title":"Detecting adjacent row anomalies","prompt":"Can you run the adjacent row changes analysis on my source_rows join coverage records? I want to see where consecutive rows have the biggest jumps. Here's the data: 2026-10-01 group-a source=100 matched=500, 2026-10-02 group-a source=95 matched=480, 2026-10-03 group-a source=200 matched=490."},{"title":"Pipeline coverage audit for two groups","prompt":"I need both a daily sum series and adjacent row changes breakdown for my matched_rows data across group-a and group-b — here are 10 rows covering the first week of October 2026, can you run those two reports together?"}],"resultDescription":"Two analytical reports: (1) a daily sum series showing aggregated values of the selected field (matched_rows or source_rows) grouped by date, and (2) an adjacent row changes report showing differences between consecutive rows for the selected field. Both reports are derived entirely from the supplied input data with no external lookups.","failureModes":["Fewer than 1 row supplied — minimum 1 row required","More than 200 rows supplied — exceeds maxItems limit","Invalid date format (must match YYYY-MM-DD pattern)","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows)","Invalid field enum value — must be 'matched_rows' or 'source_rows'","Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)","Payment failure — 0.01 USDC required per call via x402 protocol"],"whenToPreferThis":"Choose this endpoint when you have pre-assembled join coverage row data (matched_rows and source_rows) and need both a daily aggregation time series and adjacent-row change detection in a single paid call. It is ideal for data pipeline audits, ETL quality monitoring, and batch analytics on join results where you supply all data locally and need no external lookups or predictions. The bundled two-report model makes it cost-efficient compared to calling separate analytics services.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:43.131Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-daily-sum-series-adjacent-row-changes-c2eaf780"}