{"uid":"cap_Yz4gjjGvjCYAjDY5DAyns","slug":"join-coverage-duplicate-key-report-trailing-mean-series-19f6a95b","name":"Join Coverage — Duplicate Key Report + Trailing Mean Series","description":"Join coverage — Duplicate key report + Trailing mean series: Duplicate key report + Trailing mean 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-09-061?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_WhEFtZ9IwPrBByZGMQabg","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 to produce a duplicate key report and a trailing mean time series for matched_rows or source_rows data.","exampleAgentPrompt":"Run a duplicate key report and trailing mean series on my join coverage data — I have matched_rows and source_rows per date and dataset group across about 50 rows, and I want to analyze matched_rows with a window size of 7.","exampleUseCases":[{"title":"Audit ETL join for duplicate keys","prompt":"I have 80 rows of join coverage records with row IDs, dates, dataset groups, matched_rows, and source_rows — can you run a duplicate key report plus a trailing mean series on matched_rows using a window of 5?"},{"title":"Rolling average for data pipeline coverage","prompt":"Run a trailing mean series on source_rows for my join coverage records — I've got about 120 rows across two dataset groups and want a window of 10 to smooth out daily variance."},{"title":"QA join output before loading to warehouse","prompt":"Before I load this join output to the warehouse, check my 60 coverage records for duplicate keys and give me the trailing mean of matched_rows with window 3 so I can spot anomalies."}],"resultDescription":"Returns two independent analytical reports: (1) a duplicate key report identifying any row_id values that appear more than once across the supplied records, and (2) a trailing mean time series computed over the selected field (matched_rows or source_rows) using the specified rolling window size — both computed locally from the submitted data with no external lookups.","failureModes":["Input array contains more than 200 rows — request rejected","Missing required fields (row_id, dataset_group, date, matched_rows, or source_rows) in any row","Invalid date format (must match YYYY-MM-DD pattern)","Window size outside allowed range (2–200)","Empty rows array (minItems: 1 not satisfied)","Numeric values outside allowed range (±1,000,000,000,000)"],"whenToPreferThis":"Choose this endpoint when you need both duplicate key detection and rolling mean time series analysis on join coverage records in a single $0.01 call, handling up to 200 rows. It is ideal for ETL QA workflows where you want to audit join outputs for duplicated identifiers while simultaneously smoothing a numeric metric over time — all from supplied data without requiring any external data sources or live lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:26.132Z","isFirstParty":false,"canonicalSlug":"join-coverage-duplicate-key-report-trailing-mean-series-19f6a95b"}