{"uid":"cap_PJvTt3sJ7Yfme1NoGt8g8","slug":"texture-baking-analytics-adjacent-row-changes-secondary-measure-4fc443d4","name":"Texture Baking Analytics — Adjacent Row Changes & Secondary-Measure Weighted Mean","description":"Texture baking — Adjacent row changes + Secondary-measure weighted mean: Adjacent row changes + Secondary-measure weighted mean 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-10-159?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_gYiBL1cShyyPRp3d3Wakm","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 adjacent row-to-row changes and secondary-measure weighted mean statistics for texture baking records (bake_seconds, texture_pixels) across up to 200 rows.","exampleAgentPrompt":"Can you run adjacent row change analysis and a secondary-measure weighted mean on my texture baking records — I have bake_seconds and texture_pixels data for about 50 rows across two asset groups, and I want the report on the bake_seconds field?","exampleUseCases":[{"title":"Bake time drift detection across render farm","prompt":"I have 120 texture baking job records with bake_seconds and texture_pixels logged daily — can you compute the adjacent row changes in bake_seconds so I can see where bake times are spiking between consecutive jobs?"},{"title":"Weighted mean pixel density for asset groups","prompt":"I've got texture baking records for two asset groups over the past month. Can you calculate the secondary-measure weighted mean for texture_pixels across those rows so I know the average pixel density weighted by bake time?"},{"title":"Quality review of baking pipeline performance","prompt":"Here are 80 rows of texture baking data with dates, asset group labels, bake_seconds, and texture_pixels — run both the adjacent row change report and the weighted mean report on bake_seconds so I can review pipeline performance trends."}],"resultDescription":"Returns two analytical reports: (1) an adjacent row change report showing differences between consecutive row values for the selected field, and (2) a secondary-measure weighted mean report giving a weighted average using the complementary measure as weights — both computed locally against the supplied texture baking records.","failureModes":["Exceeds 200-row limit — request rejected","Missing required fields (row_id, date, bake_seconds, texture_pixels) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Null values in numeric fields may affect weighted mean computation","Invalid field enum value (not bake_seconds or texture_pixels) — rejected"],"whenToPreferThis":"Choose this endpoint when you have texture baking tabular data (up to 200 rows) and need both adjacent row-delta analysis and a secondary-measure weighted mean in a single low-cost call ($0.01 USDC for both reports). Ideal for 3D asset pipeline monitoring, render farm QA, and baking performance analysis where no external data lookup or prediction is needed — purely local computation on supplied rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:52:27.756Z","isFirstParty":false,"canonicalSlug":"texture-baking-analytics-adjacent-row-changes-secondary-measure-4fc443d4"}