{"uid":"cap_j7DfBqOg6bqusN0zOYCqG","slug":"join-coverage-analytics-duplicate-key-report-date-by-category-pivot-e86831c1","name":"Join Coverage Analytics — Duplicate Key Report + Date by Category Pivot","description":"Join coverage — Duplicate key report + Date by category pivot: Duplicate key report + Date by category pivot 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-09-068?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_2MxYHt-zBU5lUE1fG46eH","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 records (matched_rows, source_rows) to produce two reports: a duplicate key detection report and a date-by-category pivot table, for up to 200 rows.","exampleAgentPrompt":"Can you run a duplicate key report and a date-by-category pivot on my join coverage data? I have rows with row_id, dataset_group (like 'group-a' and 'group-b'), dates, matched_rows, and source_rows — analyze the matched_rows field across up to 200 rows.","exampleUseCases":[{"title":"ETL pipeline join quality audit","prompt":"I have 150 rows from my ETL join step with row_id, dataset_group, date, matched_rows, and source_rows — can you run a duplicate key report and pivot the matched_rows by date and category so I can see where joins are breaking down?"},{"title":"Daily dataset coverage monitoring","prompt":"Here are my daily join coverage records across two dataset groups for the past month. Can you check for any duplicate keys and give me a pivot of source_rows by date and dataset_group?"},{"title":"Data reconciliation anomaly detection","prompt":"I'm reconciling two data sources and want to spot duplicate row IDs and see how matched_rows trend over dates by group. Can you run the duplicate key report and date-by-category pivot on these 80 join coverage records?"}],"resultDescription":"Returns two independent analytical reports: (1) a duplicate key report identifying repeated row_ids within the supplied join coverage records, and (2) a date-by-category pivot table summarizing the selected metric (matched_rows or source_rows) broken down by date and dataset_group — all computed locally without external lookups.","failureModes":["Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors","Date strings not matching YYYY-MM-DD pattern are rejected","Submitting more than 200 rows returns an error","Empty rows array is rejected (minItems: 1)","Invalid field enum value (not 'matched_rows' or 'source_rows') causes rejection","Malformed numeric values outside allowed range cause schema validation failure"],"whenToPreferThis":"Choose this endpoint when you need both duplicate key detection and a date-by-category pivot on join coverage data in a single low-cost call. It is ideal for data engineers validating ETL join quality, reconciling datasets, or auditing coverage metrics across time and category without needing external lookups or predictions. At $0.01 USDC for two reports on up to 200 rows, it is cost-efficient for routine data quality checks.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:36.659Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-duplicate-key-report-date-by-category-pivot-e86831c1"}