{"uid":"cap_KUxTj5juO5AufZFIKtP_F","slug":"join-coverage-adjacent-row-changes-iqr-outlier-flags-7e275622","name":"Join Coverage — Adjacent Row Changes + IQR Outlier Flags","description":"Join coverage — Adjacent row changes + IQR outlier flags: Adjacent row changes + IQR outlier flags 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-09-157?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_BZ4tgFHkZEnBgyQFO0DIO","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 adjacent row change detection and IQR-based outlier flags across up to 200 rows in two independent analytical reports.","exampleAgentPrompt":"Can you analyze my join coverage data for the 'orders' dataset group and flag any adjacent row changes and IQR outliers in the matched_rows field? I have about 30 daily records from 2024-01-01 through 2024-01-30.","exampleUseCases":[{"title":"ETL pipeline join health audit","prompt":"I have 60 daily join coverage records for my ETL pipeline — can you detect any sudden day-over-day changes and IQR outliers in the matched_rows field so I can spot where the pipeline broke?"},{"title":"Dataset group anomaly comparison","prompt":"Run adjacent row change detection and IQR outlier flagging on my source_rows data for the 'customer_events' group — I have about 90 records and want to find which dates look anomalous."},{"title":"Weekly join coverage QA report","prompt":"Here are 150 join coverage rows from my data warehouse quality check — can you produce both an adjacent row change report and IQR outlier flags on matched_rows so I know which records to investigate?"}],"resultDescription":"Two independent analytical reports: (1) adjacent row changes showing how matched_rows or source_rows shifted between consecutive rows, and (2) IQR outlier flags identifying which rows fall outside the interquartile range bounds — all computed locally from the supplied data, with no external lookups.","failureModes":["Fewer than 1 row supplied — minimum row count not met","More than 200 rows supplied — exceeds maximum batch size","Missing required fields (row_id, date, matched_rows, source_rows, dataset_group) on any row","Date field does not match YYYY-MM-DD pattern — validation error","Null values in the selected field may reduce outlier detection accuracy","Payment of 0.01 USDC not completed — request rejected by x402 paywall"],"whenToPreferThis":"Choose this endpoint when you need both adjacent-row change detection and IQR outlier analysis on join coverage metrics (matched_rows, source_rows) in a single call, at low cost ($0.01 USDC for up to 200 rows). It is ideal for data quality pipelines, ETL monitoring, and dataset join audits where no external data enrichment or prediction is needed — pure local analytics on supplied records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:41.323Z","isFirstParty":false,"canonicalSlug":"join-coverage-adjacent-row-changes-iqr-outlier-flags-7e275622"}