Installation

1. 1
   Make sure Claude is on your device and in your terminal.

   Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.

   One-time setup

   Copy

   npm i -g @anthropic-ai/claude-code

   Already have it? Skip ahead.

2. 2
   Paste into Claude Code or into your terminal.

   Install

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   git clone ht••••••••••••••••••••••••••••••• •••••••••••••••• •• ••••• •• ••••••••••••••••••••••••••••••••• •• •• •• ••••••••••••••••••••••••••••••••••••••••• ••••••••••••••••••••••••••••••••••

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   This copies the whole skill folder into ~/.claude/skills/yao-audio-yaoapp/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

   Faster alternative (instruction-only skills)

   Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

   Quick install (SKILL.md only)

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   mkdir -p ~/.•••••••••••••••••••••••••••••• •• •••• ••••• ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• •• ••••••••••••••••••••••••••••••••••••••••••

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3. 3
   Restart Claude Code.

   Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.

4. 4
   Just ask Claude.

   Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

Audio expert. ALWAYS invoke this skill when the user asks to transcribe, recognize, or convert speech/audio to text.

What this skill does

tai tool audio_transcribe --audio_path /path/to/meeting.m4a

tai tool audio_transcribe --audio_path /path/to/recording.wav --language en --provider llm.my-openai:whisper-1

tai tool audio_providers