{"uid":"cap_IytELloVkSvx5lhU1Yqpn","slug":"join-coverage-record-quality-audit-and-keyed-dataset-comparison-3111ff4d","name":"Join Coverage Record Quality Audit and Keyed Dataset Comparison","description":"Join coverage — Record quality audit + Keyed dataset comparison: Record quality audit + Keyed dataset comparison 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-09-018?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}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"matched_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_rows":1,"matched_rows":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_rows":2,"matched_rows":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"other":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","matched_rows","source_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","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":21,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":17,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":33,"dataset_group":"group-b"}],"maxItems":200,"minItems":0}}},"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_IhMQxcrkMvpxYwagb1ND3","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":"Runs two local analytical reports on join coverage data: a record quality audit and a keyed dataset comparison between two supplied datasets (rows vs other), for up to 200 rows each.","exampleAgentPrompt":"Can you run a record quality audit and keyed comparison on my join coverage data? I have two datasets — the primary has rows for group-a and group-b from 2026-10-01 to 2026-10-04 with matched_rows and source_rows counts, and the secondary has slightly different matched_rows values for the same row IDs — please give me both reports.","exampleUseCases":[{"title":"ETL pipeline join coverage audit","prompt":"I just ran our nightly ETL and have join coverage logs for the last 7 days across two dataset groups. Can you audit the record quality and flag any rows where matched_rows or source_rows look problematic? Here are the records with row_id, date, dataset_group, matched_rows, and source_rows."},{"title":"Comparing two versions of join output","prompt":"We have yesterday's join coverage snapshot and today's — both with the same row IDs and groups. Can you compare them side by side and tell me where the matched_rows or source_rows differ between the two versions?"},{"title":"Match rate anomaly detection across groups","prompt":"I want to check whether our group-a and group-b datasets have any suspicious records where the matched_rows count is way off from source_rows. Can you run a quality audit on both my primary and secondary join coverage datasets — I'll provide up to 50 rows in each."}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit identifying data issues, nulls, or anomalous values in the join coverage records, and (2) a keyed dataset comparison report showing differences between the primary (rows) and secondary (other) datasets on matched_rows and source_rows fields — all computed locally without external lookups.","failureModes":["Input arrays exceed 200 rows — request rejected","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) on any row causes validation error","Date fields not matching YYYY-MM-DD pattern cause schema rejection","Empty rows array (minItems: 1 not met) causes failure","Numeric values outside ±1 trillion range rejected"],"whenToPreferThis":"Choose this endpoint when you need offline, deterministic analytical reports on join coverage data — specifically both a record quality audit AND a keyed cross-dataset comparison in a single call. Ideal for data engineers validating ETL outputs, comparing pipeline snapshots, or auditing match rates without needing real-time lookups or external enrichment. Prefer this over general-purpose analytics when your data is already structured as join coverage records with matched_rows and source_rows fields.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:34.860Z","isFirstParty":false,"canonicalSlug":"join-coverage-record-quality-audit-and-keyed-dataset-comparison-3111ff4d"}