{"uid":"cap_CfS6KnmNklM_kGi36UTRJ","slug":"texture-baking-numeric-distribution-and-iqr-outlier-flags-3e09604b","name":"Texture Baking Numeric Distribution and IQR Outlier Flags","description":"Texture baking — Numeric distribution + IQR outlier flags: Numeric distribution + IQR outlier flags for supplied texture baking records (bake_seconds, texture_pixels). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-creative-10-080?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","bake_seconds","texture_pixels"],"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},"bake_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"texture_pixels":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","asset_group":"group-a","bake_seconds":10,"texture_pixels":1},{"date":"2026-10-02","row_id":"row-2","asset_group":"group-b","bake_seconds":20,"texture_pixels":2},{"date":"2026-10-03","row_id":"row-3","asset_group":"group-a","bake_seconds":15,"texture_pixels":3},{"date":"2026-10-04","row_id":"row-4","asset_group":"group-b","bake_seconds":30,"texture_pixels":4}],"maxItems":200,"minItems":1},"field":{"enum":["bake_seconds","texture_pixels"],"type":"string","default":"bake_seconds"}}},"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_Dwo_f6foY2TtjF8aoU4B0","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":"Computes numeric distribution statistics and IQR-based outlier flags for texture baking records (bake_seconds or texture_pixels) over up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"Analyze the distribution and flag IQR outliers for my texture baking records — here are 10 rows with bake_seconds and texture_pixels values across two asset groups, and I want the report on bake_seconds specifically.","exampleUseCases":[{"title":"Outlier detection in baking pipeline","prompt":"I have 150 texture baking job records from last week with bake_seconds and texture_pixels. Can you run the IQR outlier detection on bake_seconds and show me which rows are flagged as anomalies?"},{"title":"Distribution summary for pixel counts","prompt":"Give me a numeric distribution report for texture_pixels across these 80 baking records — I want to understand the spread and see if any rows are outside the normal IQR range."},{"title":"QA audit on asset group bake times","prompt":"Here are my texture baking logs for group-a and group-b with dates and bake_seconds — run the distribution and IQR outlier analysis on bake_seconds so I can identify jobs that took unusually long."}],"resultDescription":"Returns two analytical reports per call: (1) a numeric distribution summary (min, max, mean, median, quartiles, standard deviation, etc.) and (2) IQR-based outlier flags per row, identifying which records fall outside the interquartile range bounds — all computed locally on the supplied data without any external lookups.","failureModes":["Empty or missing rows array returns validation error","More than 200 rows submitted exceeds limit and is rejected","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Non-numeric values in bake_seconds or texture_pixels may be treated as null","Invalid field enum value (not bake_seconds or texture_pixels) causes rejection","row_id missing or empty string fails minLength constraint"],"whenToPreferThis":"Choose this endpoint when you need fast, local statistical analysis of texture baking pipeline data — specifically IQR-based outlier detection and numeric distribution summaries for bake_seconds or texture_pixels — without requiring any external data lookup or ML model. Best suited for QA audits, pipeline monitoring, and data validation workflows in 3D rendering or game development contexts where you have up to 200 structured baking records ready to submit.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-27T00:44:51.208Z","isFirstParty":false,"canonicalSlug":"texture-baking-numeric-distribution-and-iqr-outlier-flags-3e09604b"}