{"uid":"cap_5KRdwmqqZy7uA88Gfg_-w","slug":"uv-layouts-record-quality-audit-string-normalisation-iqr-outlier-flags-7bb34751","name":"UV Layouts — Record Quality Audit + String Normalisation + IQR Outlier Flags","description":"UV layouts — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags 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-06-203?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_bi32Z5UV26REbhLKLYk6B","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":"Audits up to 200 UV layout records for quality issues, normalises string fields, and flags numeric outliers using IQR analysis across island_count and occupied_percent fields.","exampleAgentPrompt":"Can you audit these UV layout records for data quality issues, normalise the string fields, and flag any IQR outliers in the island_count column? I have about 50 rows with row_id, asset_group, date, island_count, and occupied_percent values.","exampleUseCases":[{"title":"Pre-pipeline UV layout data validation","prompt":"Before I run my UV layout pipeline, can you check this batch of 120 UV layout records for quality issues, normalise the asset_group strings, and flag any outliers in island_count using IQR analysis?"},{"title":"Occupied percent anomaly detection","prompt":"I've got a dataset of UV layout records and I'm worried some occupied_percent values are way off — can you run the quality audit and IQR outlier flags on the occupied_percent field for all 80 rows?"},{"title":"Asset group string cleaning audit","prompt":"My UV layout export from last week has inconsistent asset_group labels across 60 rows — can you run a string normalisation and record quality audit on it, and also flag any island_count outliers while you're at it?"}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit identifying missing, malformed, or invalid field values; (2) a string normalisation report showing standardised versions of text fields like asset_group; and (3) an IQR-based outlier flag report identifying rows with statistically anomalous values in the selected numeric field (island_count or occupied_percent). All analysis is performed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Invalid date format (not YYYY-MM-DD) causes row-level validation failure","Missing required fields (row_id, asset_group, date, island_count, occupied_percent) cause row rejection","Invalid field selector enum value (not island_count or occupied_percent) causes error","Empty rows array causes immediate failure","Numeric values outside allowed range cause validation errors"],"whenToPreferThis":"Choose this endpoint when you need a combined data quality audit, string normalisation, and IQR outlier detection in a single call for UV layout records specifically containing island_count and occupied_percent metrics. It is ideal for pre-processing pipelines where you want three analytical reports in one low-cost API call without any external data lookups or predictions. Prefer it over single-report alternatives when you need all three analyses simultaneously on datasets up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-27T06:54:32.175Z","isFirstParty":false,"canonicalSlug":"uv-layouts-record-quality-audit-string-normalisation-iqr-outlier-flags-7bb34751"}