{"uid":"cap_G50ItK3CLQmAT2zF0uBvS","slug":"uv-layouts-data-quality-suite-record-audit-string-normalisation-8b1217bc","name":"UV Layouts Data Quality Suite — Record Audit, String Normalisation & Deduplication","description":"UV layouts — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication 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-06-191?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}}},"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_qbv5UYYrGsu-4Pba2nhoU","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 analytical reports on UV layout records: a record quality audit, string normalisation, and exact row deduplication, against fields island_count and occupied_percent.","exampleAgentPrompt":"Can you audit the quality of my UV layout data, normalise the strings, and remove any exact duplicate rows? I have up to 50 rows with fields like row_id, asset_group, date, island_count, and occupied_percent that I want cleaned up.","exampleUseCases":[{"title":"Pre-pipeline UV layout data cleanup","prompt":"I have a batch of 80 UV layout records with island_count and occupied_percent values and I'm seeing some messy strings and possible duplicates — can you run a full quality audit, normalise all the text fields, and flag any exact duplicate rows before I load them into the database?"},{"title":"Validating UV layout export before reporting","prompt":"Before I send this UV layout export to the client, can you check these 120 rows for data quality issues, make sure all the string fields are normalised, and confirm there are no duplicate entries across island_count and occupied_percent?"},{"title":"Debugging bad UV layout ingestion","prompt":"Something went wrong in our UV layout ingestion pipeline and I think we have dirty data — can you audit these 35 records for quality problems, normalise the asset_group strings, and tell me if any rows are exact duplicates?"}],"resultDescription":"Returns three independent reports: (1) a record quality audit flagging missing, null, or out-of-range values across all fields; (2) a string normalisation report showing transformed text fields such as asset_group; and (3) an exact row deduplication report identifying and listing duplicate rows. All reports are generated locally without external lookups.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, date, island_count, occupied_percent) causes row-level rejection","Malformed date strings not matching YYYY-MM-DD pattern fail schema validation","Empty rows array returns an error","Numeric values outside the allowed range trigger schema rejection"],"whenToPreferThis":"Choose this endpoint when you need a combined, cost-effective data quality pass on UV layout records — specifically when you need all three operations (quality audit, string normalisation, and exact deduplication) run together in a single call for up to 200 rows. Ideal for pre-ingestion data cleaning or pre-reporting validation of UV layout datasets with island_count and occupied_percent metrics.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-27T00:44:45.954Z","isFirstParty":false,"canonicalSlug":"uv-layouts-data-quality-suite-record-audit-string-normalisation-8b1217bc"}