{"uid":"cap_FLmf8Jfns3YJgTaoFtp-q","slug":"material-libraries-string-normalisation-and-secondary-measure-85ba1694","name":"Material Libraries String Normalisation and Secondary-Measure Weighted Mean","description":"Material libraries — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied material libraries records (material_count, texture_mb). 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-03-034?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","material_count","texture_mb"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"texture_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"asset_group":{"type":"string","default":"","maxLength":80},"material_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","texture_mb":1,"asset_group":"group-a","material_count":10},{"date":"2026-10-02","row_id":"row-2","texture_mb":2,"asset_group":"group-b","material_count":20},{"date":"2026-10-03","row_id":"row-3","texture_mb":3,"asset_group":"group-a","material_count":15},{"date":"2026-10-04","row_id":"row-4","texture_mb":4,"asset_group":"group-b","material_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["material_count","texture_mb"],"type":"string","default":"material_count"}}},"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_O57QCjPQspQa2pDi-cfHS","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":"Performs string normalisation and secondary-measure weighted mean analysis on material library records (material_count, texture_mb) for up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"Normalise the asset_group strings and compute a secondary-measure weighted mean for material_count across my material library rows — I've got about 50 records with row IDs, dates in YYYY-MM-DD format, asset group labels, material counts, and texture sizes in MB. Can you run both the string normalisation and weighted mean reports in one call?","exampleUseCases":[{"title":"3D Game Asset Library Audit","prompt":"I have 120 rows of material library data for our game assets — each with a row ID, date, asset group name, material count, and texture size in MB. Can you normalise the asset group strings and compute a weighted mean of material_count for me, and give me both reports?"},{"title":"Texture Budget Analysis by Group","prompt":"We're reviewing texture memory usage across our material libraries. I have about 80 records with asset_group, date, material_count, and texture_mb fields. Please normalise the group name strings and give me the secondary-measure weighted mean for texture_mb."},{"title":"Material Count Consistency Check","prompt":"Before we ship our asset pack, I need to clean up the asset_group labels and compute a weighted average of material_count across up to 200 material library rows — dates are formatted as YYYY-MM-DD. Run string normalisation and the weighted mean report on this dataset."}],"resultDescription":"Two analytical reports per call: (1) normalised string output for the asset_group field across submitted rows, and (2) a secondary-measure weighted mean computed for the selected numeric field (material_count or texture_mb) across up to 200 rows. No external lookups or predictions are made — all computation is performed locally on the supplied data.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, asset_group, date, material_count, texture_mb) causes rejection","Invalid date format (non-YYYY-MM-DD) fails schema validation","Numeric values outside the allowed range cause schema rejection","Empty rows array is not accepted (minItems: 1)","Invalid field enum value (anything other than material_count or texture_mb) is rejected"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and secondary-measure weighted mean computed together on material library records in a single low-cost call (0.01 USDC for two reports). It is best suited for offline or batch analytical workflows on up to 200 rows of 3D asset or material library data where no live lookup, prediction, or external action is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T12:42:49.227Z","isFirstParty":false,"canonicalSlug":"material-libraries-string-normalisation-and-secondary-measure-85ba1694"}