{"uid":"cap_Cml2B7bO7HMk9LzKcG1D-","slug":"join-coverage-analytics-record-quality-audit-string-normalisation-e6e0aabd","name":"Join Coverage Analytics: Record Quality Audit, String Normalisation & Duplicate Key Report","description":"Join coverage — Record quality audit + String normalisation + Duplicate key report: Record quality audit + String normalisation + Duplicate key report 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-09-192?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}}},"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_XzeFZjU1KOGcgnJQYsoxQ","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 local analytical reports on join coverage data (matched_rows, source_rows): a record quality audit, string normalisation, and duplicate key detection — for up to 200 rows.","exampleAgentPrompt":"Can you run a full record quality audit, string normalisation, and duplicate key check on my join coverage data? I have 4 rows: row-1 on 2026-10-01 with source_rows=1, matched_rows=10 in group-a; row-2 on 2026-10-02 with source_rows=2, matched_rows=20 in group-b; row-3 on 2026-10-03 with source_rows=3, matched_rows=15 in group-a; and row-4 on 2026-10-04 with source_rows=4, matched_rows=30 in group-b.","exampleUseCases":[{"title":"ETL pipeline join audit","prompt":"I've just run a join between two datasets and have the row counts for 50 records — can you audit the record quality, normalise any string fields like dataset group names, and flag any duplicate row IDs? Here are my matched_rows and source_rows by date and group."},{"title":"Data quality check before reporting","prompt":"Before I send this join coverage summary to my analytics team, can you run a quality audit and duplicate key report on these 120 rows of matched_rows and source_rows data across our dataset groups from October 2026?"},{"title":"String normalisation for group labels","prompt":"My join coverage data has inconsistent capitalisation and spacing in the dataset_group field across 80 rows — can you run string normalisation on the records and also check for any duplicate row IDs while you're at it?"}],"resultDescription":"Three independent analytical reports for the submitted join coverage rows: (1) a record quality audit highlighting data issues in matched_rows and source_rows, (2) a string normalisation report cleaning up dataset_group and related string fields, and (3) a duplicate key report identifying any repeated row_id or key combinations — all computed locally without external lookups.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause row-level rejection","Invalid date format (not YYYY-MM-DD) fails schema validation","Numeric values outside the allowed range (-1T to 1T) are rejected","Empty rows array is not accepted (minItems: 1)"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical reports — quality audit, string normalisation, and duplicate key detection — on join coverage data with matched_rows and source_rows fields, all in one low-cost call. Ideal for ETL pipelines, data validation workflows, or pre-reporting checks on datasets up to 200 rows where no live lookup or external data enrichment is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:34.202Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-record-quality-audit-string-normalisation-e6e0aabd"}