{"uid":"cap_g8gjUAQGT76Upg0rPvstX","slug":"join-coverage-record-quality-audit-and-numeric-row-ordering-b17bd97a","name":"Join Coverage Record Quality Audit and Numeric Row Ordering","description":"Join coverage — Record quality audit + Numeric row ordering: Record quality audit + Numeric row ordering 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-09-007?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_U6bGP9Tji6pKdcGn067Bv","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":"Performs a record quality audit and numeric row ordering analysis on join coverage data (matched_rows, source_rows) for up to 200 rows, returning 2 independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit and numeric row ordering on these join coverage records — I have 4 rows with dataset groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, and matched_rows values of 10, 20, 15, and 30 — use matched_rows as the field for ordering?","exampleUseCases":[{"title":"ETL pipeline join coverage audit","prompt":"I just ran my ETL pipeline and have join coverage results for 8 rows across two dataset groups — can you audit the record quality and rank them numerically by matched_rows? Here are the rows: row-1 on 2024-01-01 with source_rows=100 and matched_rows=95 in group-sales, row-2 on 2024-01-02 with source_rows=200 and matched_rows=180 in group-sales, and so on for the rest."},{"title":"Data warehouse source row ordering","prompt":"I need a numeric ordering report on source_rows for my data warehouse join coverage — I have 5 records across dataset groups 'inventory' and 'orders' from 2024-03-01 to 2024-03-05. Can you also give me the quality audit for those same rows? Use source_rows as the field."},{"title":"Multi-group join match quality check","prompt":"Can you check the record quality and numerically order by matched_rows for my join coverage data? I have 6 rows split between 'customers' and 'transactions' groups, dated 2024-06-01 through 2024-06-06, with matched_rows ranging from 50 to 300 and source_rows from 60 to 350."}],"resultDescription":"Two independent analytical reports for the supplied join coverage rows: (1) a record quality audit identifying data completeness, nulls, and anomalies across matched_rows and source_rows fields, and (2) a numeric row ordering report ranking rows by the selected field (matched_rows or source_rows). Results are computed locally with no external lookups.","failureModes":["Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors","More than 200 rows submitted — request exceeds maxItems limit","Invalid date format (non-YYYY-MM-DD) rejected by pattern validation","Field selector not one of the allowed enum values ('matched_rows' or 'source_rows')","Empty rows array (minItems:1 not satisfied)","Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) rejected","Payment failure or insufficient USDC balance for the $0.01 per-call fee"],"whenToPreferThis":"Choose this endpoint when you need both a record quality audit and numeric ordering on join coverage data (matched_rows, source_rows) in a single call for up to 200 rows, without needing external data lookups or live predictions. Ideal for ETL pipeline validation, data engineering workflows, and post-join diagnostics where you want two complementary analytical views on the same dataset at minimal cost ($0.01 for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:37.864Z","isFirstParty":false,"canonicalSlug":"join-coverage-record-quality-audit-and-numeric-row-ordering-b17bd97a"}