{"uid":"cap_gUu3SWn874gaHiNkNrNSd","slug":"join-coverage-analytics-record-quality-audit-string-normalisation-bb94ec76","name":"Join Coverage Analytics: Record Quality Audit, String Normalisation & Numeric Distribution","description":"Join coverage — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution for supplied join coverage records (matched_rows, source_rows). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-193?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__GUXgFEMCfy1cxmxxVyGh","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 three independent analytical reports on join coverage data (matched_rows, source_rows): a record quality audit, string normalisation, and numeric distribution analysis — all locally, on up to 200 supplied rows.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and numeric distribution report on my join coverage data? Here are 4 rows: row-1 on 2026-10-01 in group-a with source_rows=1 and matched_rows=10, row-2 on 2026-10-02 in group-b with source_rows=2 and matched_rows=20, row-3 on 2026-10-03 in group-a with source_rows=3 and matched_rows=15, row-4 on 2026-10-04 in group-b with source_rows=4 and matched_rows=30 — analyse the matched_rows field.","exampleUseCases":[{"title":"ETL pipeline join quality check","prompt":"I just ran a data pipeline and got join coverage results across 12 dataset groups for October 2026 — can you audit the record quality, normalise the dataset_group strings, and show me the numeric distribution for matched_rows? I'll give you all the row data with their dates and counts."},{"title":"Source row completeness audit","prompt":"Can you analyse these 50 join coverage records from our data warehouse — I need a quality audit plus numeric distribution on the source_rows field to see how evenly matched our data is across groups."},{"title":"Multi-group string normalisation review","prompt":"We have join coverage rows from 8 different dataset groups with inconsistent naming — can you run string normalisation on them alongside a record quality audit and distribution check? I'm feeding you up to 80 rows with matched_rows and source_rows values by date."}],"resultDescription":"Three independent analytical reports covering: (1) a record quality audit flagging completeness and validity issues across the supplied rows, (2) string normalisation analysis of text fields like dataset_group, and (3) a numeric distribution summary of the selected field (matched_rows or source_rows). All analysis is performed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — exceeds the per-call row limit","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) on any row","Invalid date format (must match YYYY-MM-DD pattern)","Numeric values out of the allowed range (±1,000,000,000,000)","Empty rows array — minItems:1 not satisfied","Invalid field enum value (must be 'matched_rows' or 'source_rows')"],"whenToPreferThis":"Choose this endpoint when you have up to 200 join coverage records and need three simultaneous analytical perspectives — quality audit, string normalisation, and numeric distribution — in a single call without any external lookups or live data enrichment. It is ideal for offline ETL validation workflows, batch data quality reviews, and situations where all data is already in hand and needs structured local analysis for a flat $0.01 USDC fee.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:29.691Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-record-quality-audit-string-normalisation-bb94ec76"}