{"uid":"cap_6gp2WeDhskr-8cHSkzSe_","slug":"join-coverage-numeric-row-ordering-daily-sum-series-10287b90","name":"Join Coverage — Numeric Row Ordering + Daily Sum Series","description":"Join coverage — Numeric row ordering + Daily sum series: Numeric row ordering + Daily sum series 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-09-114?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_oQwItBEko0qNiJmZc_ZRI","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 numeric row ordering and daily sum time series for join coverage records (matched_rows, source_rows) across up to 200 rows, returning 2 analytical reports.","exampleAgentPrompt":"Take my join coverage data for group-a and group-b across October 2026 — rows with matched_rows and source_rows values — and give me both a numeric row ordering and a daily sum series for the matched_rows field.","exampleUseCases":[{"title":"Daily sum trend for matched rows","prompt":"I have join coverage records from my ETL pipeline for October, with matched_rows and source_rows per day across two dataset groups. Can you compute the numeric row ordering and the daily sum time series for matched_rows so I can see the trend?"},{"title":"Ranking source rows by dataset group","prompt":"Here are my join coverage records with source_rows values across several dates and groups. Give me a numeric row ordering and a daily sum series for source_rows so I can spot which days had the highest volume."},{"title":"Validating join completeness over time","prompt":"I need to audit our join coverage — I have up to 150 records each with a date, dataset_group, matched_rows, and source_rows. Run the numeric row ordering and daily sum series on matched_rows so I can see whether coverage is improving day over day."}],"resultDescription":"Returns two analytical reports for the supplied join coverage rows: (1) a numeric row ordering ranking each row by the selected field (matched_rows or source_rows), and (2) a daily sum time series aggregating the selected field by date — all computed locally without external lookups.","failureModes":["Missing required fields (row_id, date, dataset_group, matched_rows, source_rows) cause validation errors","Dates not matching YYYY-MM-DD pattern are rejected","More than 200 rows submitted exceeds the maxItems limit","Null values for matched_rows or source_rows may affect aggregation results","Invalid field enum value (not 'matched_rows' or 'source_rows') causes rejection"],"whenToPreferThis":"Choose this endpoint when you have join coverage tabular data (matched_rows, source_rows) and need both a ranked row ordering and a daily sum time series in a single call for up to 200 rows, without requiring any external data lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:26.733Z","isFirstParty":false,"canonicalSlug":"join-coverage-numeric-row-ordering-daily-sum-series-10287b90"}