{"uid":"cap_LUcQ_EPpXzFpgYLYma88w","slug":"texture-baking-analytics-base-100-series-secondary-measure-weighted-0e5249af","name":"Texture Baking Analytics — Base-100 Series + Secondary-Measure Weighted Mean","description":"Texture baking — Base-100 series + Secondary-measure weighted mean: Base-100 series + 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-10-166?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_T93N-xi9Fyq4Yf__5EWlA","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 Base-100 index series and a secondary-measure weighted mean for up to 200 texture baking records (bake_seconds, texture_pixels) using local analytical engines.","exampleAgentPrompt":"Analyze my texture baking data using a base-100 index starting from row 0 on the bake_seconds field — here are 4 records: row-1 group-a 2026-10-01 bake_seconds=10 texture_pixels=1, row-2 group-b 2026-10-02 bake_seconds=20 texture_pixels=2, row-3 group-a 2026-10-03 bake_seconds=15 texture_pixels=3, row-4 group-b 2026-10-04 bake_seconds=30 texture_pixels=4. Give me both the base-100 series and the texture_pixels weighted mean.","exampleUseCases":[{"title":"Benchmarking bake times across asset groups","prompt":"I have 50 texture baking records across two asset groups and want to see how bake_seconds evolved relative to the very first record — can you index them on a base-100 scale starting at row 0 and also give me the weighted mean for texture_pixels?"},{"title":"Tracking rendering efficiency over a production sprint","prompt":"Here are 120 daily texture baking logs from our sprint — index the texture_pixels field to base 100 starting from day 1 and compute the secondary weighted mean so I can see which asset groups are drifting from baseline."},{"title":"Comparing bake duration against pixel output","prompt":"I want two reports on my texture baking dataset of 80 rows: a base-100 series on bake_seconds anchored at row index 5, plus the weighted mean for texture_pixels across all rows — can you run both analytics?"}],"resultDescription":"Returns two analytical reports: (1) a Base-100 index series showing each row's selected field value normalized relative to the chosen base row, and (2) a secondary-measure weighted mean across all supplied rows. Both reports are computed locally from the submitted data with no external lookups.","failureModes":["More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, date, bake_seconds, or texture_pixels) — validation error","base_index out of range for the submitted row count — index error","Non-date-format string in date field — pattern validation failure","null values in both numeric fields may affect weighted mean calculation"],"whenToPreferThis":"Choose this endpoint when you have raw texture baking records (bake_seconds, texture_pixels) and need both a normalized Base-100 time series and a weighted mean in a single low-cost call. It is ideal for 3D asset pipeline analytics where no external data, predictions, or live lookups are needed — just deterministic statistical computation on your supplied dataset of up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-27T00:44:43.794Z","isFirstParty":false,"canonicalSlug":"texture-baking-analytics-base-100-series-secondary-measure-weighted-0e5249af"}