{"uid":"cap_95jda2g_vxfKVy6E8FIAC","slug":"lighting-setups-string-normalisation-date-by-category-pivot-66861316","name":"Lighting Setups String Normalisation + Date by Category Pivot","description":"Lighting setups — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied lighting setups records (light_count, render_seconds). 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-11-035?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","light_count","render_seconds"],"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},"light_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"render_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","asset_group":"group-a","light_count":10,"render_seconds":1},{"date":"2026-10-02","row_id":"row-2","asset_group":"group-b","light_count":20,"render_seconds":2},{"date":"2026-10-03","row_id":"row-3","asset_group":"group-a","light_count":15,"render_seconds":3},{"date":"2026-10-04","row_id":"row-4","asset_group":"group-b","light_count":30,"render_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["light_count","render_seconds"],"type":"string","default":"light_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_zsD3RpjtueyhlQ7tjyCmq","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 date-by-category pivot analysis on up to 200 lighting setup records containing light count and render seconds data, producing two independent analytical reports.","exampleAgentPrompt":"Can you run a string normalisation and date-by-category pivot on these lighting setup records — I have 4 rows with asset groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, light counts of 10, 20, 15, 30, and render seconds of 1, 2, 3, 4 — and analyze the light_count field?","exampleUseCases":[{"title":"Benchmarking render times by rig type","prompt":"I have 150 rows of lighting rig records with asset groups like 'studio-a' and 'outdoor-b', dates in October, and render_seconds values. Can you normalize the strings and pivot render_seconds by date and asset group so I can see which rigs are slowest?"},{"title":"Auditing light counts across scene categories","prompt":"I need two reports on my lighting scene data — about 80 rows with row IDs, asset groups, dates, and light_count values — please do string normalisation and a date-by-category pivot on the light_count field."},{"title":"Summarising CGI lighting data for a production pipeline","prompt":"We have up to 200 rows of CGI lighting setup logs with asset_group, date, light_count, and render_seconds columns. Can you run string normalization and a date-grouped category pivot on them so our team can see trends by group?"}],"resultDescription":"Two independent analytical reports: a string normalisation report (cleaned/normalized string fields from the input rows) and a date-by-category pivot report (aggregated numeric field values grouped by date and asset_group), based on the supplied lighting setup records.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Invalid date format (not YYYY-MM-DD) — row may fail validation","Missing required fields (row_id, asset_group, date, light_count, render_seconds) — row rejected","Numeric values outside allowed range (-1e12 to 1e12) — validation error","Invalid field selector value (not 'light_count' or 'render_seconds') — error returned"],"whenToPreferThis":"Choose this endpoint when you have up to 200 lighting setup records with light_count and render_seconds fields and need both string normalisation and a date-by-category pivot in a single low-cost call ($0.01 USDC). Ideal for 3D rendering pipelines, CGI production teams, or data analysts who want two local analytical reports without any external lookup, prediction, or live data dependency.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T00:49:12.269Z","isFirstParty":false,"canonicalSlug":"lighting-setups-string-normalisation-date-by-category-pivot-66861316"}