audio-quality-check
SolidAnalyzes audio recording quality - echo detection, loudness, speech intelligibility, SNR, and spectral analysis. Use when the user wants to check a recording's quality, detect echo or duplication, measure speech clarity, compare original vs processed audio, or diagnose why a recording sounds bad, including tracks from Blackbox or any call recording app.
Install
Quality Score: 85/100
Skill Content
Details
- Author
- tenequm
- Repository
- tenequm/skills
- Created
- 10 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
sound-ear
Give Claude eyes and ears on audio. Turns any audio or video's soundtrack into things Claude can actually reason over — a readable spectrogram + waveform, objective loudness/silence/scene-cut facts, a semantic "sound map" of every SFX with timestamps (Gemini on the user's Vertex, or offline CLAP), offline speech transcription, and cymatic/audio-reactive visualization renders (any aspect ratio, plus a seamless long-form loop mode). Auto-routes to whatever engines the current device supports. Use whenever the user wants Claude to listen to, evaluate, QA, or describe the sound in a render (SFX timing, "does this feel off", mix issues), analyze an audio file, or generate sound-driven visuals for content (e.g. a sleep/ambient channel).
sound-ear
Give Claude eyes and ears on audio. Turns any audio or video's soundtrack into things Claude can actually reason over — a readable spectrogram + waveform, objective loudness/silence/scene-cut facts, a semantic "sound map" of every SFX with timestamps (Gemini on the user's Vertex, or offline CLAP), offline speech transcription, and cymatic/audio-reactive visualization renders (any aspect ratio, plus a seamless long-form loop mode). Auto-routes to whatever engines the current device supports. Use whenever the user wants Claude to listen to, evaluate, QA, or describe the sound in a render (SFX timing, "does this feel off", mix issues), analyze an audio file, or generate sound-driven visuals for content (e.g. a sleep/ambient channel).
audioeditor
AI audio editing pipeline: Whisper word-level transcription → Claude segment classification (KEEP/CUT_FILLER/CUT_FALSE_START/CUT_STUTTER/CUT_DEAD_AIR) → ffmpeg with 40ms qsin crossfades and room-tone fill → optional Cleanvoice cloud polish. Distinguishes rhetorical from accidental pauses; breaths attenuated 50%. Modes: --preview, --aggressive, --polish. Workflow: Clean. USE WHEN clean audio, edit audio, remove filler words, clean podcast, remove ums, cut dead air, polish audio, trim recording, cut stutters. NOT FOR video composition (use Remotion).