{"uid":"cap_KBk9WMOs83A40qaBS3IDl","slug":"render-jobs-string-normalisation-base-100-series-4fb9468f","name":"Render Jobs String Normalisation + Base-100 Series","description":"Render jobs — String normalisation + Base-100 series: String normalisation + Base-100 series 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-02-030?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_7twqrnvrRtHVb0X94LOSe","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":"Normalises render job metrics (render_seconds, sample_count) and computes a Base-100 indexed series for up to 200 supplied rows, returning two analytical reports.","exampleAgentPrompt":"Can you normalise my render job records and produce a base-100 index series on render_seconds, using row 0 as the base? I have 4 jobs: row-1 on 2026-10-01 in group-a with 10 render seconds and 1 sample, row-2 on 2026-10-02 in group-b with 20 seconds and 2 samples, row-3 on 2026-10-03 in group-a with 15 seconds and 3 samples, and row-4 on 2026-10-04 in group-b with 30 seconds and 4 samples.","exampleUseCases":[{"title":"Benchmarking render speed across asset groups","prompt":"I want to benchmark how our render times have changed over the past week across two asset groups. Here are 8 job records with dates, render_seconds, and sample_counts — can you normalise them and give me a base-100 index on render_seconds starting from the first row?"},{"title":"Tracking sample count trends over a sprint","prompt":"Can you take these 20 render job rows from our October sprint, normalise the sample_count field, and produce a base-100 index series so I can see how sampling volume changed relative to day one?"},{"title":"Comparing rendering efficiency across two pipelines","prompt":"I have 50 render job records split between pipeline-alpha and pipeline-beta asset groups. Please string-normalise the data and build a base-100 series on render_seconds using row index 0 as the baseline so I can compare pipeline efficiency over time."}],"resultDescription":"Returns two reports: (1) string-normalised representations of the selected metric field across all supplied rows, and (2) a Base-100 indexed time series anchored at the specified base_index row, covering all submitted render job records up to 200 rows. No external data is fetched; all computation uses local analytical engines.","failureModes":["Fewer than 1 or more than 200 rows submitted — rejected with validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","base_index references a row index beyond the submitted row count — out-of-bounds error","Null values in render_seconds or sample_count may affect index computation if the base row is null","field value not in enum ['render_seconds','sample_count'] — schema validation error"],"whenToPreferThis":"Choose this endpoint when you have raw render job tabular data (up to 200 rows) and need both string normalisation and a Base-100 indexed series in a single low-cost call ($0.01 USDC). It is well-suited for offline/batch analytical reporting on rendering pipeline metrics without requiring any live data source, external lookup, or prediction. Prefer alternatives if you need more than 200 rows, live data enrichment, or statistical methods beyond normalisation and base indexing.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T00:48:44.483Z","isFirstParty":false,"canonicalSlug":"render-jobs-string-normalisation-base-100-series-4fb9468f"}