{"uid":"cap_-7GpfgCppKIQ6MCNRXKsr","slug":"audio-voices-string-normalisation-and-date-by-category-pivot-b92206d9","name":"Audio Voices String Normalisation and Date-by-Category Pivot","description":"Audio voices — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied audio voices records (active_voices, audio_cpu_ms). 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-game-10-035?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","game_area","date","active_voices","audio_cpu_ms"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"game_area":{"type":"string","default":"","maxLength":80},"audio_cpu_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"active_voices":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","game_area":"group-a","audio_cpu_ms":1,"active_voices":10},{"date":"2026-10-02","row_id":"row-2","game_area":"group-b","audio_cpu_ms":2,"active_voices":20},{"date":"2026-10-03","row_id":"row-3","game_area":"group-a","audio_cpu_ms":3,"active_voices":15},{"date":"2026-10-04","row_id":"row-4","game_area":"group-b","audio_cpu_ms":4,"active_voices":30}],"maxItems":200,"minItems":1},"field":{"enum":["active_voices","audio_cpu_ms"],"type":"string","default":"active_voices"}}},"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_KTIPKQ-kGlrzMJoqEAVTC","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 string normalisation and date-by-category pivot analytics on up to 200 supplied audio-voices records containing active_voices and audio_cpu_ms fields.","exampleAgentPrompt":"Can you run string normalisation and a date-by-category pivot on these audio voices records — I have rows with row_id, game_area, date, active_voices, and audio_cpu_ms fields — and I want the pivot done on the active_voices field?","exampleUseCases":[{"title":"Game audio performance pivot by area","prompt":"I have about 150 rows of game audio telemetry with columns row_id, game_area, date, active_voices, and audio_cpu_ms — can you normalise the strings and pivot active_voices by date and game_area so I can see which areas are heaviest?"},{"title":"CPU cost analysis across game zones","prompt":"Take these audio records for our game zones and give me a date-by-category pivot on audio_cpu_ms so I can see which game_area dates are most CPU-intensive, and clean up any string inconsistencies while you're at it."},{"title":"QA check on voice count reporting","prompt":"I need to validate and normalise our audio voice count data — here are up to 200 rows with game_area, date, and active_voices — please run the string normalisation and pivot the active_voices by date and category so I can spot anomalies."}],"resultDescription":"Two analytical reports: (1) a string-normalised version of the supplied audio voices records, and (2) a date-by-category pivot table aggregating the selected numeric field (active_voices or audio_cpu_ms) across game_area and date dimensions — all computed locally on the supplied data with no external lookups.","failureModes":["Exceeding 200 rows causes rejection or truncation","Missing required fields (row_id, game_area, date, active_voices, audio_cpu_ms) triggers validation error","Invalid date format (not YYYY-MM-DD) causes parse failure","Null-only numeric columns may produce empty pivot cells","Invalid field enum value (not active_voices or audio_cpu_ms) causes parameter error","Payment of 0.01 USDC must be included via x402 protocol or request is rejected"],"whenToPreferThis":"Choose this endpoint when you have game audio telemetry records (up to 200 rows) that need both string normalisation and a date-by-category pivot in a single low-cost call. It is purpose-built for the active_voices and audio_cpu_ms schema and returns two reports for $0.01 USDC. Prefer it over general analytics services when you already have structured rows in this exact format and need lightweight, deterministic local computation rather than ML inference or live data lookup.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:31:47.316Z","isFirstParty":false,"canonicalSlug":"audio-voices-string-normalisation-and-date-by-category-pivot-b92206d9"}