{"uid":"cap_KL55SpEHqXcnSnLcqKDpp","slug":"texture-baking-analytics-grouped-numeric-summary-secondary-measure-15216fcd","name":"Texture Baking Analytics — Grouped Numeric Summary + Secondary-Measure Weighted Mean","description":"Texture baking — Grouped numeric summary + Secondary-measure weighted mean: Grouped numeric summary + 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-10-096?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_a_7Rp12MlDxJQq-1ZCTxe","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 a grouped numeric summary and a secondary-measure weighted mean for texture baking records (bake_seconds, texture_pixels) across up to 200 rows.","exampleAgentPrompt":"I have texture baking records for two asset groups — group-a and group-b — with bake_seconds and texture_pixels columns for about 50 rows. Can you run a grouped numeric summary and a weighted mean for bake_seconds (weighted by texture_pixels) across those groups?","exampleUseCases":[{"title":"Pipeline performance audit by asset group","prompt":"I've got 120 texture baking records across four asset groups, each with bake_seconds and texture_pixels. Can you group them by asset_group and give me a numeric summary of bake_seconds plus a weighted mean using texture_pixels as the weight?"},{"title":"Comparing bake times across dates for a game project","prompt":"Here are my texture baking logs from October — about 80 rows with dates, asset_group, bake_seconds, and texture_pixels. Group them by date and asset_group and compute a summary of texture_pixels with a bake_seconds-weighted mean."},{"title":"Optimizing render farm asset throughput","prompt":"I want to understand which asset groups are taking the longest to bake textures. I have 200 rows of records with bake_seconds and texture_pixels — can you give me a grouped numeric summary by asset_group and compute the weighted mean of bake_seconds using texture_pixels as the secondary measure?"}],"resultDescription":"Returns two analytical reports: (1) a grouped numeric summary of the selected primary field (bake_seconds or texture_pixels) broken down by asset_group, and (2) a weighted mean of the primary measure using the other measure as the weight — both computed locally without any external lookups or predictions, for up to 200 input rows.","failureModes":["Input array exceeds 200 rows — request will be rejected","Missing required fields (row_id, asset_group, date, bake_seconds, texture_pixels) cause validation errors","Date values not matching YYYY-MM-DD pattern will fail schema validation","All-null values for the selected measure field may produce undefined weighted mean","Malformed JSON body returns 400-level error","Payment not provided or insufficient USDC balance causes 402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have tabular texture baking records (up to 200 rows) and need both a grouped numeric summary and a weighted mean in a single low-cost call ($0.01 USDC). It is ideal for 3D asset pipeline analytics, render farm audits, or game development workflows where bake_seconds and texture_pixels are the key metrics. Prefer this over generic analytics tools when you want a paired two-report output without setting up a data warehouse or calling an external prediction service.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-27T06:54:28.572Z","isFirstParty":false,"canonicalSlug":"texture-baking-analytics-grouped-numeric-summary-secondary-measure-15216fcd"}