How do I install the Local Tts skill?

Run npx skillmds@latest add krishagel/local-tts in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Local Tts skill do?

Local text-to-speech using MLX and Kokoro model It is listed under AI & ML on SkillMD.

Is Local Tts safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Local Tts?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Local Tts free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Local Tts?

krishagel (@krishagel) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Local Tts by krishagel — Agent Skill

Name: Local Tts
Author: krishagel

File contents

Local TTS Skill

Generate high-quality speech audio locally using Apple Silicon MLX acceleration and the Kokoro-82M model. No API keys or recurring costs.

Quick Start

# Generate MP3 from text
uv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \
    --text "Hello, this is a test." \
    --output ~/Desktop/test.mp3

# Generate from file
uv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \
    --file /tmp/script.txt \
    --voice af_heart \
    --output ~/Desktop/podcast.mp3

# List available voices
uv run --with mlx-audio skills/local-tts/scripts/list_voices.py

Parameters

Parameter	Required	Default	Description
`--text`	One of text/file	-	Text to convert
`--file`	One of text/file	-	Path to text file
`--voice`	No	`af_heart`	Voice preset
`--output`	Yes	-	Output file path (.mp3, .wav)
`--model`	No	`Kokoro-82M-bf16`	Model to use
`--list-voices`	No	-	Show available voices

Voice Presets

American English Female (prefix: af_)

af_heart - Warm, friendly (default)
af_bella - Soft, calm
af_nova - Clear, professional
af_river - Clear, confident
af_sarah - Soft, expressive

American English Male (prefix: am_)

am_adam - Clear, professional
am_echo - Deep, smooth
am_liam - Articulate, conversational
am_michael - Soft, measured

British English (prefix: bf_, bm_)

bf_emma - Clear, refined female
bm_daniel - Clear, professional male
bm_george - Distinguished male

See references/voices.md for full list.

Output Format

{
  "success": true,
  "file": "/Users/hagelk/Desktop/podcast.mp3",
  "voice": "af_heart",
  "model": "Kokoro-82M-bf16",
  "characters": 9824,
  "chunks": 20,
  "duration_seconds": 612.5,
  "generation_time": 45.2
}

Performance

Hardware	Speed	Notes
M3 Pro 36GB	~3-4x realtime	First run slower (model loading)
M1/M2 Mac Mini 8GB	~1.5x realtime	Works well for briefings
M1/M2 Mac Mini 16GB	~2x realtime	Comfortable headroom

Technical Details

Model: Kokoro-82M-bf16 (~200MB download on first run)
Sample rate: 24kHz mono
Chunking: Text split at ~400 chars per chunk for quality
Concatenation: Chunks joined seamlessly via pydub
Formats: MP3, WAV, M4A, OGG

Important Notes

MUST use --with flags - Do not use PEP 723 inline deps. mlx-audio requires uv's cached environment.
First run is slower - Model downloads ~200MB and espeak dependencies initialize.
Model cached at: ~/.cache/huggingface/hub/models--mlx-community--Kokoro-82M-bf16/

Integration with Morning Briefing

The morning-briefing skill uses this for podcast generation:

uv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \
    --file /tmp/morning_briefing_podcast.txt \
    --voice af_heart \
    --output ~/Desktop/morning_briefing.mp3

---name: local-ttsdescription: Local text-to-speech using MLX and Kokoro model---# Local TTS SkillGenerate high-quality speech audio locally using Apple Silicon MLX acceleration and the Kokoro-82M model. No API keys or recurring costs.## Quick Start```bash# Generate MP3 from textuv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \ --text "Hello, this is a test." \ --output ~/Desktop/test.mp3# Generate from fileuv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \ --file /tmp/script.txt \ --voice af_heart \ --output ~/Desktop/podcast.mp3# List available voicesuv run --with mlx-audio skills/local-tts/scripts/list_voices.py```## Parameters| Parameter | Required | Default | Description ||-----------|----------|---------|-------------|| `--text` | One of text/file | - | Text to convert || `--file` | One of text/file | - | Path to text file || `--voice` | No | `af_heart` | Voice preset || `--output` | Yes | - | Output file path (.mp3, .wav) || `--model` | No | `Kokoro-82M-bf16` | Model to use || `--list-voices` | No | - | Show available voices |## Voice Presets### American English Female (prefix: af_)- `af_heart` - Warm, friendly **(default)**- `af_bella` - Soft, calm- `af_nova` - Clear, professional- `af_river` - Clear, confident- `af_sarah` - Soft, expressive### American English Male (prefix: am_)- `am_adam` - Clear, professional- `am_echo` - Deep, smooth- `am_liam` - Articulate, conversational- `am_michael` - Soft, measured### British English (prefix: bf_, bm_)- `bf_emma` - Clear, refined female- `bm_daniel` - Clear, professional male- `bm_george` - Distinguished maleSee `references/voices.md` for full list.## Output Format```json{ "success": true, "file": "/Users/hagelk/Desktop/podcast.mp3", "voice": "af_heart", "model": "Kokoro-82M-bf16", "characters": 9824, "chunks": 20, "duration_seconds": 612.5, "generation_time": 45.2}```## Performance| Hardware | Speed | Notes ||----------|-------|-------|| M3 Pro 36GB | ~3-4x realtime | First run slower (model loading) || M1/M2 Mac Mini 8GB | ~1.5x realtime | Works well for briefings || M1/M2 Mac Mini 16GB | ~2x realtime | Comfortable headroom |## Technical Details- **Model**: Kokoro-82M-bf16 (~200MB download on first run)- **Sample rate**: 24kHz mono- **Chunking**: Text split at ~400 chars per chunk for quality- **Concatenation**: Chunks joined seamlessly via pydub- **Formats**: MP3, WAV, M4A, OGG## Important Notes1. **MUST use `--with` flags** - Do not use PEP 723 inline deps. mlx-audio requires uv's cached environment.2. **First run is slower** - Model downloads ~200MB and espeak dependencies initialize.3. **Model cached at**: `~/.cache/huggingface/hub/models--mlx-community--Kokoro-82M-bf16/`## Integration with Morning BriefingThe morning-briefing skill uses this for podcast generation:```bashuv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \ --file /tmp/morning_briefing_podcast.txt \ --voice af_heart \ --output ~/Desktop/morning_briefing.mp3```

Frequently asked questions

Local Tts