AS

    Audio Spectrogram Viz

    by TopAgent

    1

    Render audio as visual analytics with a small NumPy/SciPy pipeline: waveform, log-mel spectrogram, and spectral centroid over time, saved as PNG. Use when a use

    Secure checkout via Stripe

    0 installsSecurity scanned

    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurfMManus+14 more

    See it in action

    You say

    Analyze this recording for any silent gaps and show me the spectrogram.

    Your agent does

    I have generated a waveform and spectrogram for your audio. The analysis shows a 1.5s silent gap starting at the 4-second mark.

    MEDIA:/tmp/audio_analysis.png

    What you get

    Detect silence and clipping in audio filesVisualize frequency content of synthesized signalsCompare audio quality between two recordingsGenerate visual documentation for audio assets

    About this skill

    The problem

    Debugging audio issues like silent gaps, clipping, or frequency interference is impossible by looking at raw binary data or basic logs. Developers need a way to visually inspect audio content during automated processing or debugging sessions without opening a GUI.

    What it does

    • Generates time-domain waveforms to identify amplitude peaks and silence.
    • Produces log-mel spectrograms to visualize frequency content over time.
    • Converts compressed audio formats to mono WAV for consistent analysis.
    • Calculates RMS and peak signal levels to compare multiple audio takes.
    • Outputs high-resolution PNGs suitable for documentation or inline review.

    Frameworks & tools

    Python, NumPy, SciPy, Matplotlib, and FFmpeg.

    Why this beats prompting it yourself

    Standard LLMs cannot "see" audio files directly. This skill provides the specific signal processing pipeline needed to translate raw audio into a visual format the LLM can interpret and describe to you, ensuring math-heavy tasks like STFT windowing are handled correctly.

    Use cases

    • Identify silent segments or audio dropouts in long recordings.
    • Verify the frequency output of synthesized sounds or signal generators.
    • Compare two audio versions to detect clipping or noise floor differences.
    • Generate visual thumbnails for audio asset management systems.

    Known limitations

    Requires FFmpeg installed on the system path. Not intended for real-time metering or high-precision music transcription.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill passes our trust checks below.

    Security scanned

    Passed our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    30-day refund

    Not a fit? Get your money back

    Trust & safety

    Security scanned

    Verified clean today

    Listedtoday

    Creator

    TopAgent
    TopAgent

    770+ total installs · 53 skills on Agensi

    Frequently Asked Questions

    Browse More Skills