{"uid":"cap_zGmkDD9J-8GevEey1KnYS","slug":"render-jobs-record-quality-audit-string-normalisation-numeric-0c95789c","name":"Render Jobs — Record Quality Audit + String Normalisation + Numeric Distribution","description":"Render jobs — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution 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-02-193?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_3KgQKxpA_dj3ljLgXvYco","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 bundled analytical reports on render job records: a record quality audit, string normalisation, and numeric distribution analysis for render_seconds or sample_count fields.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and numeric distribution report on these render job records — I have up to 80 rows with row_id, asset_group, date, render_seconds, and sample_count fields, and I want the distribution focused on render_seconds?","exampleUseCases":[{"title":"Render pipeline data quality check","prompt":"I have a batch of render job logs from last month — about 150 rows each with a row_id, asset_group, date, render_seconds, and sample_count. Can you audit them for record quality issues, normalise the string fields, and show me the numeric distribution for render_seconds?"},{"title":"Sample count spread analysis for asset groups","prompt":"Here are 60 render job records across two asset groups with sample_count and render_seconds values. Run the full three-part report — quality audit, string normalisation, and numeric distribution — focused on sample_count so I can see how spread out the values are."},{"title":"Pre-delivery data validation for render studio","prompt":"Before I hand off this rendering dataset to the client, I want to make sure the data is clean. Can you do a record quality audit, normalise any inconsistent strings in the asset_group column, and give me a distribution breakdown of render_seconds for these 200 render job rows?"}],"resultDescription":"Returns three independent reports: (1) a record quality audit flagging completeness, validity, and consistency issues per row; (2) a string normalisation report for text fields like asset_group; and (3) a numeric distribution analysis (e.g. percentiles, range, frequency buckets) for the selected numeric field (render_seconds or sample_count). All reports are computed locally with no external lookups.","failureModes":["Exceeding 200 row limit returns a validation error","Missing required fields (row_id, date, render_seconds, sample_count) causes schema rejection","Invalid date format (not YYYY-MM-DD) triggers pattern validation failure","Numeric values outside ±1,000,000,000,000 bounds are rejected","Empty rows array returns a minItems validation error","Unrecognised field enum value (not render_seconds or sample_count) causes rejection"],"whenToPreferThis":"Choose this endpoint when you need a bundled, cost-efficient three-in-one analysis of render job records — quality audit, string normalisation, and numeric distribution — all in a single call for up to 200 rows. Ideal for creative/media pipeline QA workflows where render_seconds and sample_count are the primary metrics, and no external data sources or live predictions are needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T12:43:29.403Z","isFirstParty":false,"canonicalSlug":"render-jobs-record-quality-audit-string-normalisation-numeric-0c95789c"}