Enables AI agents to analyze audio files, extracting tempo, key, beat drops, volume surges, high tones, loudness, brightness, and structure, and returning structured JSON and visualizations.
Enables AI models to analyze audio files through numerical fingerprints, pitch tracking, and visual spectrograms without requiring direct audio playback. It provides tools for comparing audio iterations and detecting patterns using token-efficient analysis operations.
Enables LLMs to analyze music (genre, mood, tempo, key), separate audio stems, detect AI-generated music, and measure loudness using IRCAM Amplify's audio processing APIs.
Enables local, private analysis of YouTube URLs and local audio files to extract BPM, key modulations, vocal presence, transient punch, stereo width, and CLAP vibe embeddings, returning structured sonic signatures for AI agents and CLI users.
Enables comprehensive audio file analysis and metadata extraction with specialized game audio development features, supporting batch processing of multiple formats and providing platform-specific optimization recommendations.