{"uid":"cap_-EtUrxBSNl5aMfzil2OTx","slug":"lighting-setups-record-quality-audit-string-normalisation-category-30caaf09","name":"Lighting Setups — Record Quality Audit + String Normalisation + Category Frequencies","description":"Lighting setups — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies for supplied lighting setups records (light_count, render_seconds). 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-11-195?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}}},"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_MVykBxc8cKrKb_p_q2pEV","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 submitted lighting setup records: a record quality audit, string normalisation, and category frequency analysis for light_count and render_seconds fields.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and category frequency analysis on my lighting setup records? I have rows with fields like row_id, asset_group, date, light_count, and render_seconds — here are up to 200 rows to check.","exampleUseCases":[{"title":"Audit 3D scene lighting data quality","prompt":"I have a batch of lighting setup records from our rendering pipeline — each row has a row_id, asset_group, date, light_count, and render_seconds. Can you audit them for quality issues, normalise any inconsistent strings in asset_group, and tell me the frequency of each category?"},{"title":"Detect missing values in render records","prompt":"We've exported about 150 rows of lighting setup data and I suspect there are nulls and formatting inconsistencies in the light_count and asset_group fields. Can you run a record quality audit and string normalisation on these rows and report back what you find?"},{"title":"Summarise asset group distributions in lighting data","prompt":"For my creative team's post-render review, can you analyse these lighting setup records and give me a category frequency breakdown showing how many renders fall under each asset_group, along with a quality audit of the data?"}],"resultDescription":"Returns three independent reports: (1) a record quality audit flagging issues such as nulls, out-of-range values, and malformed dates; (2) a string normalisation report showing standardised versions of text fields like asset_group; and (3) a category frequency report counting occurrences of each category across the submitted rows — all computed locally without external lookups.","failureModes":["Rows array exceeds 200 items — request rejected","Missing required fields (row_id, asset_group, date, light_count, render_seconds) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers schema rejection","light_count or render_seconds outside allowed numeric range returns error","Empty rows array (minItems:1 violated) causes failure","Payment of 0.01 USDC not provided or rejected — 402 response"],"whenToPreferThis":"Choose this endpoint when you need three bundled data-quality reports (quality audit, string normalisation, category frequencies) on lighting setup records with light_count and render_seconds fields, at low cost per call, without requiring any external lookup, live data, or prediction capabilities. Ideal for post-export data validation of creative/rendering pipeline data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T18:55:19.328Z","isFirstParty":false,"canonicalSlug":"lighting-setups-record-quality-audit-string-normalisation-category-30caaf09"}