{"uid":"cap_J_hz_N1P709KSioVoUf2k","slug":"join-coverage-analytics-duplicate-key-report-numeric-row-ordering-0693d6c5","name":"Join Coverage Analytics: Duplicate Key Report + Numeric Row Ordering","description":"Join coverage — Duplicate key report + Numeric row ordering: Duplicate key report + 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-09-058?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_qZcQf00VclhMSHsagQ2pK","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 data (matched_rows, source_rows) to produce a duplicate key report and numeric row ordering for up to 200 supplied rows.","exampleAgentPrompt":"Can you run a duplicate key report and numeric row ordering on my join coverage data? I have 4 rows: row-1 on 2026-10-01 with source_rows=1 and matched_rows=10 in group-a, row-2 on 2026-10-02 with source_rows=2 and matched_rows=20 in group-b, row-3 on 2026-10-03 with source_rows=3 and matched_rows=15 in group-a, and row-4 on 2026-10-04 with source_rows=4 and matched_rows=30 in group-b — analyze by matched_rows.","exampleUseCases":[{"title":"Auditing join key uniqueness in ETL pipeline","prompt":"I need to check my ETL join results for duplicate keys — here are 50 rows with row_id, dataset_group, date, source_rows, and matched_rows values. Run a duplicate key report and rank them numerically by source_rows so I can see which rows have repeated identifiers."},{"title":"Validating matched row counts across dataset groups","prompt":"Can you analyze these 120 join coverage records across groups A and B for duplicate keys and give me a numeric ordering by matched_rows? I want to spot which row IDs appear more than once and how the match counts rank."},{"title":"Ordering join coverage rows for QA review","prompt":"For our data quality review, run a duplicate key report and numeric row ordering on these 30 join coverage rows — use matched_rows as the field — so we can prioritize which records to investigate first."}],"resultDescription":"Returns two independent analytical reports: (1) a duplicate key report identifying any repeated row identifiers within the supplied join coverage records, and (2) a numeric row ordering ranking rows by the selected field (matched_rows or source_rows). Both reports are computed locally against the supplied data with no external lookups.","failureModes":["Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) causes validation error","More than 200 rows submitted exceeds maxItems limit","Date values not matching YYYY-MM-DD pattern are rejected","Payment failure or insufficient USDC balance blocks request","Null numeric values in the selected field may affect ordering output"],"whenToPreferThis":"Choose this endpoint when you need to simultaneously check for duplicate row keys AND get a numeric ordering of join coverage records in a single API call. It is purpose-built for join coverage data with matched_rows and source_rows fields, processes up to 200 rows, and bundles two analytical reports for $0.01 USDC — ideal for lightweight data quality checks on join outputs without needing a full data warehouse or external analytics service.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:40.767Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-duplicate-key-report-numeric-row-ordering-0693d6c5"}