{"uid":"cap_mKOzzaz8VdUWgtgWuQpyU","slug":"join-coverage-record-quality-audit-category-frequencies-44f7b4e1","name":"Join Coverage Record Quality Audit & Category Frequencies","description":"Join coverage — Record quality audit + Category frequencies: Record quality audit + Category frequencies 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-09-006?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}}},"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_X_DrjbLnm5RakdYm7kfAK","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: a record quality audit and a category frequency breakdown for matched_rows and source_rows across up to 200 rows.","exampleAgentPrompt":"Can you run a record quality audit and category frequency report on my join coverage data? I have 4 rows: row-1 (group-a, 2026-10-01, source_rows=1, matched_rows=10), row-2 (group-b, 2026-10-02, source_rows=2, matched_rows=20), row-3 (group-a, 2026-10-03, source_rows=3, matched_rows=15), row-4 (group-b, 2026-10-04, source_rows=4, matched_rows=30).","exampleUseCases":[{"title":"ETL pipeline join quality check","prompt":"I ran a nightly ETL join and got these results for four rows across two dataset groups — can you audit the record quality and tell me the category frequencies for matched vs source rows? row-1 (group-a, 2026-10-01, source=500, matched=480), row-2 (group-b, 2026-10-01, source=1200, matched=950), row-3 (group-a, 2026-10-02, source=510, matched=500), row-4 (group-b, 2026-10-02, source=1180, matched=1100)."},{"title":"Data warehouse join coverage audit","prompt":"We're validating our data warehouse joins for last quarter — can you run both the record quality audit and category frequency report on these 5 join coverage records across our sales and inventory groups?"},{"title":"Detecting anomalous match rates by group","prompt":"I suspect some dataset groups have unusually high or low match rates in our join output — run a quality audit and frequency breakdown on these 10 rows so I can spot anomalies before we promote the dataset to production."}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit identifying issues such as null values, out-of-range counts, or malformed records within the supplied join coverage rows; and (2) a category frequency summary showing how matched_rows and source_rows are distributed across dataset_group values and dates. Both reports are computed locally using shared analytical engines with no external lookups.","failureModes":["Supplying more than 200 rows will be rejected — stay within the maxItems limit","Rows missing required fields (row_id, dataset_group, date, matched_rows, source_rows) will cause validation errors","Dates not matching YYYY-MM-DD format will fail schema validation","Numeric values outside the allowed range (-1T to +1T) will be rejected","Empty rows array will fail minItems constraint"],"whenToPreferThis":"Choose this endpoint when you need a quick, low-cost dual-report analysis on join coverage data — specifically when you want both a record quality audit and category frequency breakdown computed together in a single call for up to 200 rows, with no need for live lookups or external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:46.083Z","isFirstParty":false,"canonicalSlug":"join-coverage-record-quality-audit-category-frequencies-44f7b4e1"}