{"uid":"cap_m_YoGj_JMIiSMnxW14CDX","slug":"texture-baking-analytics-string-normalisation-category-frequencies-faff2b17","name":"Texture Baking Analytics — String Normalisation + Category Frequencies","description":"Texture baking — String normalisation + Category frequencies: String normalisation + Category frequencies 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-10-024?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}}},"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_L92XIQOdz7NN_n90pG-6L","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 two local analytical reports on texture baking records: string normalisation of text fields and category frequency counts for asset groups, using up to 200 supplied rows.","exampleAgentPrompt":"Can you run string normalisation and category frequency analysis on my texture baking records? I have up to 50 rows with fields like row_id, asset_group, date, bake_seconds, and texture_pixels — here's the data.","exampleUseCases":[{"title":"Asset group distribution audit","prompt":"I have 80 texture baking records across different asset groups with bake_seconds and texture_pixels values — can you tell me how the records are distributed across each asset group and normalise the asset group name strings?"},{"title":"Pipeline data quality check","prompt":"Before I hand off my texture baking dataset to the rendering team, can you normalise all the string fields and give me a frequency count of each category so I can spot any inconsistencies? I have about 120 rows with row_id, asset_group, date, bake_seconds, and texture_pixels."},{"title":"Bake job summary for studio report","prompt":"I need a quick summary of our texture baking jobs this quarter — can you normalise the asset group labels and count how many jobs fell into each category? I'll send you the records with bake_seconds and texture_pixels included."}],"resultDescription":"Two analytical reports: (1) string-normalised versions of text fields (row_id, asset_group, date) in the supplied rows, and (2) category frequency counts showing how many records belong to each asset_group value — all computed locally from the supplied data with no external lookups.","failureModes":["More than 200 rows supplied — request will be rejected or truncated","Missing required fields (row_id, bake_seconds, texture_pixels) cause row-level errors","Invalid date format (not YYYY-MM-DD) may cause parsing issues","Null numeric values for bake_seconds or texture_pixels may be excluded from numeric summaries","Empty or whitespace-only asset_group values may produce ambiguous category buckets"],"whenToPreferThis":"Choose this endpoint when you have up to 200 texture baking records and need both string normalisation of categorical fields and a frequency breakdown of asset groups in a single low-cost call ($0.01 USDC). It is best for offline/batch analytical use where no live lookup, prediction, or external data enrichment is needed — purely local computation on supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T12:43:14.458Z","isFirstParty":false,"canonicalSlug":"texture-baking-analytics-string-normalisation-category-frequencies-faff2b17"}