{"uid":"cap_CAAr_R95eOUvHdA7i3Lw_","slug":"material-libraries-string-normalisation-trailing-mean-series-5d310dad","name":"Material Libraries — String Normalisation + Trailing Mean Series","description":"Material libraries — String normalisation + Trailing mean series: String normalisation + Trailing mean series 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-03-028?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_k4Ugv8ufBaOEvLvWZuETv","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 trailing mean series analytics on material library records (material_count, texture_mb) for up to 200 rows, returning two reports per call.","exampleAgentPrompt":"Can you run string normalisation and trailing mean series on my material library data? I have 4 rows with material_count values (10, 20, 15, 30) and texture_mb values (1, 2, 3, 4) across asset groups 'group-a' and 'group-b' from 2026-10-01 to 2026-10-04 — use material_count as the field and a window of 2.","exampleUseCases":[{"title":"Smooth material count trends over time","prompt":"I've got a week's worth of material library records with daily material_count readings across two asset groups. Can you compute a trailing mean series with a window of 3 so I can see smoothed trends, and also give me normalised string values for the counts?"},{"title":"Texture MB rolling average for asset audit","prompt":"I need to analyze texture_mb data for my material library — 10 rows across different asset groups with dates from 2026-09-01 to 2026-09-10. Run the trailing mean with a window of 2 on texture_mb and include the string normalisation report too."},{"title":"Normalise material data for cross-group comparison","prompt":"Can you normalise the material_count field across these 8 material library rows from my different asset groups and also give me the trailing mean series with a window of 4, so I can compare groups on a level playing field?"}],"resultDescription":"Returns two analytical reports for the submitted material library rows: (1) string normalisation output for the selected field values, and (2) a trailing mean series computed over the specified window size — both derived locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — request rejected","Window size larger than the number of rows — trailing mean may be undefined or partial","Invalid date format (not YYYY-MM-DD) — validation error","Null values in the selected field — may produce incomplete or partial trailing mean","Missing required row fields (row_id, asset_group, date) — schema validation failure","Field value not 'material_count' or 'texture_mb' — enum validation error"],"whenToPreferThis":"Use this endpoint when you have up to 200 material library records and need both string normalisation and trailing mean series computed in a single low-cost call ($0.01 USDC). Ideal for game or 3D asset pipelines where you want to smooth and normalise material_count or texture_mb metrics without setting up a local analytics stack. Prefer this over general-purpose analytics tools when working specifically with asset group data keyed by date and row ID.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-31T12:41:28.047Z","isFirstParty":false,"canonicalSlug":"material-libraries-string-normalisation-trailing-mean-series-5d310dad"}