{"uid":"cap_M0jOjvA3rl9-dfp7e42em","slug":"uv-layouts-data-quality-audit-record-quality-string-normalisation-444db7a2","name":"UV Layouts Data Quality Audit — Record Quality, String Normalisation & Adjacent Row Changes","description":"UV layouts — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied uv layouts records (island_count, occupied_percent). 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-creative-06-200?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","island_count","occupied_percent"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"asset_group":{"type":"string","default":"","maxLength":80},"island_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"occupied_percent":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","asset_group":"group-a","island_count":10,"occupied_percent":1},{"date":"2026-10-02","row_id":"row-2","asset_group":"group-b","island_count":20,"occupied_percent":2},{"date":"2026-10-03","row_id":"row-3","asset_group":"group-a","island_count":15,"occupied_percent":3},{"date":"2026-10-04","row_id":"row-4","asset_group":"group-b","island_count":30,"occupied_percent":4}],"maxItems":200,"minItems":1},"field":{"enum":["island_count","occupied_percent"],"type":"string","default":"island_count"}}},"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_zu-5kL_PFDTLBn6uhFu3o","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 (record quality audit, string normalisation, and adjacent row change detection) on up to 200 rows of UV layout data containing island_count and occupied_percent fields.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and adjacent row change check on my UV layout records? I have 4 rows for group-a and group-b from 2026-10-01 to 2026-10-04, with island_count values of 10, 20, 15, and 30, and I want the analysis run on the island_count field.","exampleUseCases":[{"title":"UV layout pipeline data quality gate","prompt":"Before I push my UV layout data downstream, can you audit these 50 rows for record quality issues, normalise the asset_group strings, and flag any big jumps between adjacent rows in the island_count field?"},{"title":"Detecting sudden changes in occupancy metrics","prompt":"I've got 150 rows of UV layout data with occupied_percent values and I want to know if there are any sudden jumps between consecutive rows — can you also check overall record quality and clean up any string inconsistencies in the asset_group column?"},{"title":"QA check on exported UV layout dataset","prompt":"I exported 80 UV layout rows from our tool and I'm worried the data might have nulls, dirty strings, or weird step-changes in the occupied_percent column — can you run the three-report quality check on this dataset?"}],"resultDescription":"Three separate analytical reports delivered together: (1) a record quality audit flagging nulls, out-of-range values, and other data issues; (2) a string normalisation report for text fields like asset_group; and (3) an adjacent row change report highlighting step-changes or anomalies between consecutive rows in the selected numeric field (island_count or occupied_percent). All analysis is performed locally on the supplied rows with no external lookups.","failureModes":["More than 200 rows submitted — request rejected with validation error","Invalid date format (not YYYY-MM-DD) causes row-level rejection","Missing required fields (row_id, date, asset_group) causes validation failure","Invalid field enum value (not island_count or occupied_percent) causes error","Empty rows array rejected (minItems: 1)","Numeric values outside allowed range cause validation errors"],"whenToPreferThis":"Choose this endpoint when you need three combined analytical reports (quality audit, string normalisation, adjacent row change detection) for UV layout records in a single low-cost call. It is best when your dataset is already collected and you need offline/local analysis without any live lookups, predictions, or external integrations. Prefer it over individual single-report endpoints when you need all three report types on the same dataset to save cost and round-trips.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-27T00:44:26.953Z","isFirstParty":false,"canonicalSlug":"uv-layouts-data-quality-audit-record-quality-string-normalisation-444db7a2"}