{"uid":"cap_w3DOkEQWMBwiG643WcNEM","slug":"join-coverage-analytics-numeric-distribution-adjacent-row-changes-25b84361","name":"Join Coverage Analytics: Numeric Distribution + Adjacent Row Changes","description":"Join coverage — Numeric distribution + Adjacent row changes: Numeric distribution + Adjacent row changes 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-09-077?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_2hvWJGJ72ivruEo-cbBUR","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) by producing two local analytical reports: a numeric distribution summary and an adjacent row change analysis, for up to 200 rows.","exampleAgentPrompt":"Can you analyze these 4 join coverage rows for me — I want both a numeric distribution and adjacent row change report on the matched_rows field: row-1 on 2026-10-01 (source=1, matched=10, group=group-a), row-2 on 2026-10-02 (source=2, matched=20, group=group-b), row-3 on 2026-10-03 (source=3, matched=15, group=group-a), row-4 on 2026-10-04 (source=4, matched=30, group=group-b)?","exampleUseCases":[{"title":"Pipeline join quality audit","prompt":"I have daily join coverage logs for two dataset groups over the past week — can you give me a numeric distribution and row-by-row change report on the matched_rows field so I can see where match rates jumped or dropped?"},{"title":"ETL anomaly detection review","prompt":"Here are 50 rows of source_rows and matched_rows from our nightly ETL job — run both the distribution and adjacent change analysis on source_rows so I can spot any anomalies between consecutive runs."},{"title":"Multi-group coverage comparison","prompt":"I've got join coverage data across three dataset groups for Q4 — can you profile the numeric distribution and show me where adjacent row changes are largest for the matched_rows column?"}],"resultDescription":"Returns two analytical reports computed locally from the supplied rows: (1) a numeric distribution summary of the selected field (matched_rows or source_rows), including statistics like min, max, mean, percentiles, and frequency; (2) an adjacent row change analysis showing delta values between consecutive rows ordered by date, highlighting increases and decreases in the selected metric. Both reports cover up to 200 input rows.","failureModes":["Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) returns a validation error","Exceeding 200 rows causes rejection — trim input to 200 rows max","Invalid date format (not YYYY-MM-DD) triggers a schema validation failure","Empty rows array returns an error — at least 1 row required","Null numeric values may reduce statistical coverage in distribution report"],"whenToPreferThis":"Choose this endpoint when you have tabular join coverage data (matched_rows, source_rows) and need both a numeric distribution profile and a sequential row-change analysis in a single low-cost call. It is ideal for pipeline monitoring, ETL auditing, and data quality checks where you want offline/local analytics without external lookups. Prefer this over general-purpose analytics APIs when you specifically need join coverage metrics profiled across dataset groups with no side effects.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T07:19:37.352Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-numeric-distribution-adjacent-row-changes-25b84361"}