{"uid":"cap_IKTVo2oNTLMjoqn2ZFQvT","slug":"compositing-graphs-string-normalisation-date-by-category-pivot-0ce0e8c0","name":"Compositing Graphs String Normalisation + Date by Category Pivot","description":"Compositing graphs — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied compositing graphs records (node_count, render_seconds). 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-09-035?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","node_count","render_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"node_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"asset_group":{"type":"string","default":"","maxLength":80},"render_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","node_count":10,"asset_group":"group-a","render_seconds":1},{"date":"2026-10-02","row_id":"row-2","node_count":20,"asset_group":"group-b","render_seconds":2},{"date":"2026-10-03","row_id":"row-3","node_count":15,"asset_group":"group-a","render_seconds":3},{"date":"2026-10-04","row_id":"row-4","node_count":30,"asset_group":"group-b","render_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["node_count","render_seconds"],"type":"string","default":"node_count"}}},"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_KVkFtmt367t7rmGq4B6kO","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 two analytical reports on compositing graph records: string normalisation and date-by-category pivot for node_count or render_seconds metrics, supporting up to 200 rows.","exampleAgentPrompt":"I have compositing graph data with node counts and render times across asset groups — can you run both a string normalisation report and a date-by-category pivot on it, focusing on the node_count field? Here are my rows: group-a on 2026-10-01 had 10 nodes and 1 render second, group-b on 2026-10-02 had 20 nodes and 2 seconds, and so on.","exampleUseCases":[{"title":"Render time pivot by asset group","prompt":"I've got daily compositing records for two asset groups over the past month — can you pivot the render_seconds values by asset group and date, and also normalize the string fields? Here's the data: row-1, group-a, 2026-10-01, 10 nodes, 1.5 seconds; row-2, group-b, 2026-10-01, 25 nodes, 3.2 seconds."},{"title":"Node count trend analysis across groups","prompt":"Can you run string normalisation and a date-by-category pivot on my compositing graph data focusing on node_count? I want to see how node counts differ between group-a and group-b over October 2026 — I have about 50 rows to analyze."},{"title":"Pipeline QA reporting for render metrics","prompt":"For our compositing pipeline QA, I need both a string normalisation report and a date-by-category pivot on render_seconds for these asset groups. Can you process up to 150 rows of compositing graph records covering group-a, group-b, and group-c from last quarter?"}],"resultDescription":"Returns two independent analytical reports: (1) a string normalisation report cleaning and standardising text fields in the compositing graph records, and (2) a date-by-category pivot table aggregating the selected metric (node_count or render_seconds) across asset groups and dates. Both reports are derived locally from the supplied data with no external lookups.","failureModes":["Rows array empty or missing — validation error","More than 200 rows submitted — exceeds maximum limit","Invalid date format (not YYYY-MM-DD) — schema validation failure","Field value not in enum ['node_count','render_seconds'] — rejected","Numeric values outside ±1,000,000,000,000 bounds — schema error","Missing required fields (row_id, asset_group, date) — validation failure","Payment not included or insufficient — 402 response"],"whenToPreferThis":"Choose this endpoint when you have compositing graph records (with node_count and render_seconds metrics) and need both string normalisation and a date-by-category pivot in a single low-cost call. It is ideal for creative pipeline analytics involving up to 200 rows of asset group data where no external lookup or prediction is needed — just local statistical transformation of supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T00:49:05.391Z","isFirstParty":false,"canonicalSlug":"compositing-graphs-string-normalisation-date-by-category-pivot-0ce0e8c0"}