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Extract Audio

Community
gupsammy
extract-audio

This skill should be used when the user asks to "extract audio", "get the mp3", "strip audio from video", "rip audio", "save audio from video", "convert to audio", "get the soundtrack", "pull the audio track", "save as mp3", "export audio", or "separate audio from video".

Overview

Publishergupsammy
RepositoryClaudest
Skill nameextract-audio
Stars
275
Forks
16
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by gupsammy on GitHub. Read the source before you install it.

Installation

Install the Extract Audio AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/gupsammy/Claudest/tree/main/plugins/claude-content/skills/extract-audio
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/gupsammy/Claudest.git /tmp/Claudest
mkdir -p .claude/skills
cp -r /tmp/Claudest/plugins/claude-content/skills/extract-audio .claude/skills/extract-audio
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Extract Audio in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Extract Audio on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Extract Audio is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Format Decision Tree

User wantsFormatFlagsWhy
Music, archive qualityFLAC-c:a flacLossless, no quality loss
Music, small + transparentMP3 VBR-c:a libmp3lame -q:a 0~200kbps avg, perceptually lossless
Podcast / voiceMP3 128k CBR-c:a libmp3lame -b:a 128kSufficient for speech, universally compatible
Mobile / streamingAAC 192k-c:a aac -b:a 192kBetter than MP3 at equivalent bitrate
DAW / editingWAV-c:a pcm_s16le -ar 44100No encoding loss, widest DAW support
Source already target formatCopy-c:a copyNo re-encode, instant, lossless

Process

1. Probe audio streams

bash
ffprobe -v quiet -print_format json -show_streams "$INPUT" | \
  python3 -c "
import json, sys
streams = [s for s in json.load(sys.stdin)['streams'] if s['codec_type']=='audio']
for i, s in enumerate(streams):
    print(f'Stream {i}: {s[\"codec_name\"]} {s.get(\"bit_rate\",\"?\")} bps {s.get(\"channel_layout\",\"?\")}')
"

2. Determine format

Apply the decision tree above if the user didn't specify. If the source audio codec already matches the target, use -c:a copy to avoid transcoding.

If multiple audio streams exist, ask the user which to extract — or use -map 0:a to extract all. Once the user responds, apply -map 0:a:N (where N is the zero-based stream index they chose) or -map 0:a for all streams in the Phase 3 command.

3. Construct command

bash
# General pattern (-vn drops the video stream entirely):
ffmpeg -i "$INPUT" -vn [FORMAT_FLAGS] "$OUTPUT"

# Examples:
ffmpeg -i video.mp4 -vn -c:a libmp3lame -q:a 0 audio.mp3        # MP3 VBR best quality
ffmpeg -i video.mp4 -vn -c:a libmp3lame -b:a 128k podcast.mp3   # MP3 128k CBR
ffmpeg -i video.mp4 -vn -c:a flac archive.flac                   # FLAC lossless
ffmpeg -i video.mp4 -vn -c:a aac -b:a 192k mobile.aac           # AAC
ffmpeg -i video.mp4 -vn -c:a pcm_s16le -ar 44100 edit.wav       # WAV for DAW
ffmpeg -i video.mp4 -vn -c:a copy original.m4a                  # Copy audio stream

4. Confirm and run

Show: detected source codec and bitrate, chosen output format, output path. Wait for approval, then run.

Report output file size and duration: ffprobe -v quiet -show_format "$OUTPUT" | grep -E "duration|size"

Key Decisions

Preserve generation quality: avoid transcoding chains that degrade source fidelity. Each decision below is an application of this principle.

  • Lossy-to-lossy warning: if the source is already lossy (MP3, AAC, OGG) and the user wants a different lossy format, warn them that re-encoding degrades quality. Recommend keeping the source format or using -c:a copy where container compatibility allows.
  • For files >1 hour, ask whether the user wants the full file or a specific range — trimming can be added with -ss and -to before -vn.
  • M4A vs AAC: AAC is the codec, M4A is the container. Use .m4a extension for Apple device compatibility; use .aac for a raw stream.

Frequently asked questions

What does the Extract Audio AI skill do?

This skill should be used when the user asks to "extract audio", "get the mp3", "strip audio from video", "rip audio", "save audio from video", "convert to audio", "get the soundtrack", "pull the audio track", "save as mp3", "export audio", or "separate audio from video".

Why use Extract Audio on TypingMind?

Because you install it once and use it with any model. Extract Audio is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Extract Audio in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gupsammy/Claudest/tree/main/plugins/claude-content/skills/extract-audio. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Extract Audio?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Extract Audio?

As many as you like. As long as a model supports skills, you can use Extract Audio with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Extract Audio AI skill free?

It is published on GitHub by gupsammy. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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