{"uid":"cap_AaMUOZw81BO2Uw9izKhMy","slug":"texture-baking-data-quality-audit-string-normalisation-secondary-307b1945","name":"Texture Baking Data Quality Audit + String Normalisation + Secondary-Measure Weighted Mean","description":"Texture baking — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean for supplied texture baking records (bake_seconds, texture_pixels). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-creative-10-205?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_QK4l8LiHP-teNxeyHZVyy","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":"Runs three analytical reports on texture baking records: a record quality audit, string normalisation, and a secondary-measure weighted mean — all computed locally without external lookups.","exampleAgentPrompt":"Can you run the quality audit, string normalisation, and weighted mean reports on my texture baking data? Here are up to 200 rows with fields row_id, asset_group, date, bake_seconds, and texture_pixels — use bake_seconds as the secondary measure field.","exampleUseCases":[{"title":"QA pass on baking pipeline output","prompt":"I've got a batch of texture baking records — row IDs, asset groups, dates, bake_seconds, and texture_pixels. Can you audit the record quality, normalise the asset group strings, and give me a weighted mean for bake_seconds across all the rows?"},{"title":"Weighted mean for texture pixel counts","prompt":"Run the three-report analysis on my texture baking dataset — I want the quality audit, string normalisation, and the weighted mean computed for texture_pixels. Here are 150 rows covering multiple asset groups."},{"title":"Pre-pipeline data validation for a render job","prompt":"Before I hand off these texture baking records to the next stage, can you do a quality audit, clean up the string fields, and compute the weighted mean for bake_seconds so I can sanity-check the batch? I have about 80 rows."}],"resultDescription":"Returns three independent analytical reports for the submitted texture baking rows: (1) a record quality audit flagging issues such as missing or malformed values, (2) normalised string representations of categorical fields like asset_group, and (3) a weighted mean computed for the selected secondary measure field (bake_seconds or texture_pixels).","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, date, bake_seconds, texture_pixels) cause row-level errors","Malformed date strings (not YYYY-MM-DD) fail schema validation","Payment of 0.01 USDC not completed results in 402 response","Numeric values outside the allowed range trigger validation rejection"],"whenToPreferThis":"Choose this endpoint when you need all three of a record quality audit, string normalisation, and weighted mean in a single call for texture baking data (bake_seconds and texture_pixels), and your dataset fits within 200 rows. It is a self-contained local computation requiring no external data sources, making it fast and deterministic. Prefer this over general-purpose analytics tools when you specifically work in a 3D texture baking or rendering pipeline context.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T00:49:24.686Z","isFirstParty":false,"canonicalSlug":"texture-baking-data-quality-audit-string-normalisation-secondary-307b1945"}