{"uid":"cap_r-L58P8THIltS5NCJ2g_H","slug":"texture-baking-analytics-string-normalisation-secondary-measure-a4b0ff56","name":"Texture Baking Analytics — String Normalisation + Secondary-Measure Weighted Mean","description":"Texture baking — String normalisation + Secondary-measure weighted mean: String normalisation + 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-10-034?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__F1AiOj-7AFxHI7HibnYO","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 string normalisation and secondary-measure weighted mean analytics for texture baking records (bake_seconds, texture_pixels) across up to 200 rows.","exampleAgentPrompt":"Can you run string normalisation and secondary-measure weighted mean reports on these texture baking records — I have 4 rows with asset groups 'group-a' and 'group-b', bake_seconds values like 10, 20, 15, 30, and texture_pixels values 1 through 4, and I want to analyze bake_seconds?","exampleUseCases":[{"title":"Bake time normalisation across asset groups","prompt":"I have a set of texture baking records for two asset groups — can you normalise the bake_seconds strings and give me a weighted mean report? I've got rows dated from 2026-10-01 through 2026-10-04 with bake times ranging from 10 to 30 seconds and I want to focus on the bake_seconds field."},{"title":"Texture pixel weighted mean summary","prompt":"Run the secondary-measure weighted mean analysis on my texture baking dataset — I have about 50 rows across several asset groups with texture_pixels measurements and I need a summary report using texture_pixels as the target field."},{"title":"Multi-group baking quality audit","prompt":"I need two analytical reports on my texture baking batch — string normalisation plus weighted mean — for around 100 rows covering multiple asset groups with both bake_seconds and texture_pixels data, using bake_seconds as the primary field to analyze."}],"resultDescription":"Two analytical reports: (1) string normalisation results for the supplied texture baking records, and (2) a secondary-measure weighted mean computed across bake_seconds or texture_pixels values, grouped by asset metadata. Results are derived entirely from the submitted data with no external lookups.","failureModes":["More than 200 rows submitted — request rejected with validation error","Missing required fields (row_id, date, bake_seconds, texture_pixels) — row-level validation failure","Invalid date format (not YYYY-MM-DD) — schema validation error","Null values in both numeric fields for all rows — weighted mean cannot be computed","Invalid field enum value (not bake_seconds or texture_pixels) — rejected with enum error"],"whenToPreferThis":"Choose this endpoint when you have texture baking tabular data (up to 200 rows) and need both string normalisation and a secondary-measure weighted mean in a single low-cost call ($0.01 USDC for two reports). Best suited for offline/batch analytical workflows over submitted data rather than live lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T00:49:26.802Z","isFirstParty":false,"canonicalSlug":"texture-baking-analytics-string-normalisation-secondary-measure-a4b0ff56"}