{"uid":"cap_eeviM5cwI7kFJ6bdgzegE","slug":"audio-voices-string-normalisation-numeric-interval-filter-c4626faf","name":"Audio Voices — String Normalisation + Numeric Interval Filter","description":"Audio voices — String normalisation + Numeric interval filter: String normalisation + Numeric interval filter 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-10-026?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_xR8cmit2m-m8btN3r6OaD","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 string fields and filters audio voice records by a numeric interval for active_voices or audio_cpu_ms, returning up to 2 analytical reports for up to 200 rows of supplied data.","exampleAgentPrompt":"I have game audio voice records for October 2026 across group-a and group-b areas — can you normalise the string fields and filter the active_voices column to only keep rows between 10 and 25, across these 4 rows of data?","exampleUseCases":[{"title":"Filter game audio voices by activity range","prompt":"Here are 50 rows of game audio log data with active_voices and audio_cpu_ms — can you normalise the strings and give me only the records where active_voices is between 5 and 30?"},{"title":"CPU ms outlier removal for audio engine","prompt":"I've got 120 audio performance records from different game areas and I want to clean the string fields and filter out any rows where audio_cpu_ms is outside 0 to 500 — can you run that analysis?"},{"title":"Pre-processing audio data for QA review","prompt":"Before I hand these audio voice logs to the QA team, can you normalise all the text fields and flag which of the 80 rows have active_voices falling between 15 and 100? I'll supply the full dataset."}],"resultDescription":"Two analytical reports covering: (1) string-normalised versions of the supplied audio voice records (game_area and other string fields cleaned), and (2) rows filtered to those where the selected numeric field (active_voices or audio_cpu_ms) falls within the specified minimum–maximum interval. Up to 200 input rows processed; results returned directly with no external lookups.","failureModes":["Fewer than 1 row supplied — validation error","More than 200 rows submitted — rejected, exceeds row limit","Invalid date format (not YYYY-MM-DD) — schema validation failure","Numeric field values outside ±1,000,000,000,000 — rejected","Field enum value other than active_voices or audio_cpu_ms — invalid input","Minimum greater than maximum — may return empty filter result","Missing required row fields (row_id, game_area, date) — schema error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of game audio voice records (with active_voices and/or audio_cpu_ms fields) and need both string normalisation and numeric interval filtering in a single cheap call ($0.01 USDC for 2 reports). It is purely local/analytical — no external lookups, predictions, or side effects — making it ideal for pre-processing or QA steps in a data pipeline. Prefer it over generic data tools when you specifically need these two operations applied to audio voice game telemetry data together.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-04T13:08:56.154Z","isFirstParty":false,"canonicalSlug":"audio-voices-string-normalisation-numeric-interval-filter-c4626faf"}