{"uid":"cap_kMtppoNmThFitAIiNPbQT","slug":"join-coverage-analytics-record-quality-audit-string-normalisation-ef8ff15c","name":"Join Coverage Analytics: Record Quality Audit, String Normalisation & Numeric Row Ordering","description":"Join coverage — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering 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-09-196?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_Zyf0Bw5ygZT2RWMhjx23z","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 user-supplied join coverage data (matched_rows, source_rows): a record quality audit, string normalisation, and numeric row ordering — for up to 200 rows per call.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and numeric row ordering on my join coverage data? I have 4 rows — row-1 on 2026-10-01 with source_rows=1 and matched_rows=10 in group-a, row-2 on 2026-10-02 with source_rows=2 and matched_rows=20 in group-b, row-3 on 2026-10-03 with source_rows=3 and matched_rows=15 in group-a, row-4 on 2026-10-04 with source_rows=4 and matched_rows=30 in group-b — and sort by matched_rows.","exampleUseCases":[{"title":"ETL pipeline join quality check","prompt":"I just ran an ETL join and have these 5 rows of coverage data — row-1 through row-5 across groups alpha and beta, dates from 2025-01-01 to 2025-01-05, with source_rows ranging 10–50 and matched_rows ranging 8–45. Can you audit their record quality, normalise the group name strings, and order them by source_rows?"},{"title":"Data team coverage report review","prompt":"We need to validate our weekly join coverage batch before the Monday review — here are 12 rows with row IDs, dataset groups, dates in 2025-03, and matched_rows plus source_rows values. Run the quality audit, string normalisation, and numeric ordering on matched_rows so the team can see any issues."},{"title":"Spotting nulls and bad values in join metrics","prompt":"Some of our join coverage records might have null or out-of-range values in matched_rows — can you audit the record quality and also give me string normalisation and numeric ordering for these 8 rows, sorted by matched_rows, so I can find the problematic ones?"}],"resultDescription":"Three structured analytical reports for the supplied join coverage rows: (1) a record quality audit flagging nulls, out-of-range values, and format issues; (2) a string normalisation report for dataset_group and other string fields; and (3) a numeric row ordering report ranking rows by the selected field (matched_rows or source_rows). All computed locally with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — validation error","Row missing required fields (row_id, dataset_group, date, matched_rows, source_rows) — schema rejection","Date field not in YYYY-MM-DD format — pattern validation failure","Numeric field exceeds ±1,000,000,000,000 — range error","Invalid field enum value (not matched_rows or source_rows) — enum validation error","Payment of 0.01 USDC not received — 402 Payment Required"],"whenToPreferThis":"Choose this endpoint when you need three bundled local analytical reports (quality audit, string normalisation, numeric ordering) on join coverage data in a single low-cost call, without any external lookups or live data enrichment. It is best suited for ETL validation workflows, data engineering pipelines, and pre-load data quality checks where matched_rows and source_rows are the core metrics.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:43.131Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-record-quality-audit-string-normalisation-ef8ff15c"}