{"uid":"cap_0t30ONCpiE5NyJkRUt6kK","slug":"render-jobs-data-quality-audit-string-normalisation-daily-sum-series-45c32c3b","name":"Render Jobs Data Quality Audit + String Normalisation + Daily Sum Series","description":"Render jobs — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series 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-02-198?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_KPqMjIvk7uY264bC0qNl6","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 render job records — a record quality audit, string normalisation, and a daily sum time series — for up to 200 rows of render_seconds or sample_count data.","exampleAgentPrompt":"Can you audit my render job data, normalise the asset group strings, and give me a daily sum series for render_seconds? Here are 4 rows: row-1 on 2026-10-01 for group-a with render_seconds=10 and sample_count=1, row-2 on 2026-10-02 for group-b with render_seconds=20 and sample_count=2, row-3 on 2026-10-03 for group-a with render_seconds=15 and sample_count=3, row-4 on 2026-10-04 for group-b with render_seconds=30 and sample_count=4.","exampleUseCases":[{"title":"Pipeline output data quality check","prompt":"I've got 150 rows of render job logs from last week with row IDs, asset groups, dates, render_seconds and sample_counts — can you run a quality audit on them, normalise the asset group strings, and show me a daily sum for render_seconds?"},{"title":"Daily render time aggregation for billing","prompt":"Take these render job records for October and give me a daily sum series on render_seconds so I can see total rendering time per day — also flag any quality issues or inconsistent string formatting in the asset group field."},{"title":"Sample count anomaly detection prep","prompt":"Before I hand off this dataset of 80 render job rows to finance, can you audit the record quality, clean up the asset group names, and produce a daily sum series for sample_count so we can spot any unusual spikes?"}],"resultDescription":"Returns three bundled reports: (1) a record quality audit flagging issues such as nulls, out-of-range values, and malformed dates; (2) normalised string representations of the asset_group field; and (3) a daily aggregated sum series for the chosen numeric field (render_seconds or sample_count), all computed locally with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows supplied — request rejected","date field does not match YYYY-MM-DD pattern — validation error","row_id missing or empty — schema validation failure","numeric field values outside allowed range (±1,000,000,000,000) — rejected","field enum value other than render_seconds or sample_count — invalid input error","Payment of 0.01 USDC not completed — 402 Payment Required response"],"whenToPreferThis":"Choose this endpoint when you need all three of a quality audit, string normalisation, and daily sum series on render job data in a single low-cost call ($0.01 USDC). It is ideal for pipelines that produce render_seconds or sample_count logs by asset group and date, and where offline analytical processing (no live lookups or external calls) is sufficient. It covers up to 200 rows per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T12:42:55.387Z","isFirstParty":false,"canonicalSlug":"render-jobs-data-quality-audit-string-normalisation-daily-sum-series-45c32c3b"}