{"uid":"cap_I5Sxdb7I20bLWR9YdfnKy","slug":"render-jobs-quality-audit-iqr-outlier-detection-1685997e","name":"Render Jobs Quality Audit & IQR Outlier Detection","description":"Render jobs — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied render jobs records (render_seconds, sample_count). 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-02-014?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_HPVJzBpOJy3TJb9-VtamW","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 a record-level quality audit and IQR-based outlier flagging on up to 200 render job rows (render_seconds, sample_count), returning two independent analytical reports.","exampleAgentPrompt":"Can you audit these render job records for data quality issues and flag any IQR outliers in render_seconds? I have 50 rows with row_id, asset_group, date, render_seconds, and sample_count.","exampleUseCases":[{"title":"Render pipeline data quality audit","prompt":"I have a batch of 120 render job records with render_seconds and sample_count fields — can you run a quality audit and flag any rows that look like IQR outliers in render_seconds?"},{"title":"Detect anomalous sample counts in asset groups","prompt":"I exported 80 render job logs across two asset groups, group-alpha and group-beta, from last week. Can you audit the data quality and flag any outliers in sample_count using IQR?"},{"title":"Pre-delivery render data validation","prompt":"Before I hand off this render job dataset to the client, can you check it for quality issues and identify any statistically unusual values in render_seconds across all 150 rows?"}],"resultDescription":"Two independent analytical reports: (1) a record-level quality audit covering issues such as missing values, invalid ranges, and formatting problems for each row; and (2) IQR-based outlier flags per row for the selected numeric field (render_seconds or sample_count), identifying which records fall outside the interquartile range bounds. Results are computed locally with no external data lookups.","failureModes":["Fewer than 1 row submitted returns a validation error","More than 200 rows submitted exceeds the batch limit","Missing required fields (row_id, date, render_seconds, sample_count) cause row-level rejection","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","All-null numeric column prevents IQR computation","Payment not processed causes x402 payment-required response"],"whenToPreferThis":"Choose this endpoint when you need a fast, inexpensive ($0.01 USDC) offline quality audit and IQR outlier detection on render job data specifically containing render_seconds and sample_count fields, with up to 200 rows, and no need for external data enrichment, predictions, or live lookups. Ideal for validating render pipeline exports before downstream processing.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T12:43:28.563Z","isFirstParty":false,"canonicalSlug":"render-jobs-quality-audit-iqr-outlier-detection-1685997e"}