{"uid":"cap_smLv5APQWKPddiBHVYe1E","slug":"render-jobs-record-quality-audit-string-normalisation-grouped-numeric-91668a28","name":"Render Jobs — Record Quality Audit + String Normalisation + Grouped Numeric Summary","description":"Render jobs — Record quality audit + String normalisation + Grouped numeric summary: Record quality audit + String normalisation + Grouped numeric summary for supplied render jobs records (render_seconds, sample_count). 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-02-194?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","render_seconds","sample_count"],"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},"sample_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","sample_count":1,"render_seconds":10},{"date":"2026-10-02","row_id":"row-2","asset_group":"group-b","sample_count":2,"render_seconds":20},{"date":"2026-10-03","row_id":"row-3","asset_group":"group-a","sample_count":3,"render_seconds":15},{"date":"2026-10-04","row_id":"row-4","asset_group":"group-b","sample_count":4,"render_seconds":30}],"maxItems":200,"minItems":1},"field":{"enum":["render_seconds","sample_count"],"type":"string","default":"render_seconds"}}},"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_d2gAn9PcqoUmY49_sFBXd","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 local analytical reports on render job records: a data quality audit, string normalisation, and a grouped numeric summary of render_seconds or sample_count fields.","exampleAgentPrompt":"Can you run a data quality audit, string normalisation, and grouped numeric summary on my render job records? I have up to 50 rows with render_seconds and sample_count fields grouped by asset_group, and I want to analyse render_seconds.","exampleUseCases":[{"title":"Render pipeline data quality check","prompt":"I've got a batch of render job logs with render_seconds and sample_count for different asset groups — can you audit them for data quality issues, normalise the string fields, and give me a grouped summary of render_seconds across my asset groups?"},{"title":"Detecting bad data before aggregation","prompt":"Before I roll up my render job stats, can you check these 120 render records for missing values or quality issues, normalise any inconsistent asset_group strings, and show me a grouped numeric summary so I know what I'm working with?"},{"title":"Asset group performance comparison","prompt":"I want to compare rendering performance across asset groups — can you take these render job rows and give me a quality audit, clean up the string fields, and produce a grouped summary of sample_count by asset_group?"}],"resultDescription":"Returns three independent reports for up to 200 render job rows: (1) a record quality audit identifying missing, null, or invalid values; (2) a string normalisation report standardising text fields like asset_group; and (3) a grouped numeric summary aggregating the chosen field (render_seconds or sample_count) by category. All processing is local with no external lookups.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds limit","Invalid date format (not YYYY-MM-DD) — validation error","Missing required fields (row_id, asset_group, date, render_seconds, sample_count) — schema error","Invalid field selector (not render_seconds or sample_count) — enum error","Numeric values outside allowed range — rejected"],"whenToPreferThis":"Choose this endpoint when you have render job tabular data and need three simultaneous analytical reports — quality audit, string normalisation, and grouped numeric summary — in a single low-cost call. Ideal for pre-analysis data hygiene and exploratory summarisation of creative pipeline metrics without requiring external lookup or prediction services.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T12:42:18.727Z","isFirstParty":false,"canonicalSlug":"render-jobs-record-quality-audit-string-normalisation-grouped-numeric-91668a28"}