skill-kokoro-tts-tool

name	skill-kokoro-tts-tool
description	Local text-to-speech using Kokoro TTS

When to use

• When you need to convert text to speech locally (no API keys)
• When you need to generate audio from long documents (books, articles)
• When you need seamless audiobook rendering without pop artifacts
• When you need fast offline TTS rendering (20-50x real-time)

kokoro-tts-tool Skill

Purpose

This skill provides access to the kokoro-tts-tool CLI for local text-to-speech synthesis using the Kokoro-82M model. Runs entirely on-device with ONNX runtime, optimized for Apple Silicon.

When to Use This Skill

Use this skill when:

• Converting text to speech without cloud APIs
• Generating audio from markdown/text documents
• Creating audiobooks from long-form content
• Needing 60+ voices across 8 languages

Do NOT use this skill for:

• Cloud-based TTS services
• Real-time voice conversion
• Speech-to-text (transcription)

CLI Tool: kokoro-tts-tool

Local text-to-speech CLI using Kokoro-82M (82 million parameters).

Installation

# Clone and install
git clone https://github.com/dnvriend/kokoro-tts-tool.git
cd kokoro-tts-tool
uv tool install .

Prerequisites

• Python 3.14+
• uv package manager
• Apple Silicon Mac (recommended)

Quick Start

# Initialize (downloads ~350MB models)
kokoro-tts-tool init

# Synthesize text to speakers
kokoro-tts-tool synthesize "Hello world"

# Save to file
kokoro-tts-tool synthesize "Hello" --output speech.wav

# Stream a document
kokoro-tts-tool infinite --input book.md

Progressive Disclosure

📖 Core Commands (Click to expand)

init - Download TTS Models

Downloads the Kokoro ONNX model (~300MB) and voice embeddings (~50MB).

Usage:

kokoro-tts-tool init [OPTIONS]

Options:

• --force, -f: Re-download models even if they exist

Examples:

# Download models (skips if already present)
kokoro-tts-tool init

# Force re-download
kokoro-tts-tool init --force

---

synthesize - Convert Text to Speech

Synthesizes text using the Kokoro TTS model. Audio can be played through speakers or saved to file.

Usage:

kokoro-tts-tool synthesize [TEXT] [OPTIONS]

Arguments:

• TEXT: Text to synthesize (optional if using --stdin)

Options:

• --stdin, -s: Read text from stdin
• --voice, -v VALUE: Voice ID (default: af_heart)
• --output, -o PATH: Save to WAV file
• --speed FLOAT: Speech speed 0.5-2.0 (default: 1.0)
• --silence INT: Trailing silence in ms (default: 200)

Examples:

# Play text with default voice
kokoro-tts-tool synthesize "Hello world"

# Use different voice
kokoro-tts-tool synthesize "Hello" --voice am_adam

# Save to file
kokoro-tts-tool synthesize "Hello" --output speech.wav

# Read from stdin
echo "Hello world" | kokoro-tts-tool synthesize --stdin

# Adjust speed
kokoro-tts-tool synthesize "Hello" --speed 1.5

# Multiple options
cat article.txt | kokoro-tts-tool synthesize --stdin \
    --voice bf_emma \
    --output article.wav \
    --speed 0.9

Output: Audio played through speakers (default) or saved as WAV file (24kHz, mono, 16-bit).

---

infinite - Stream Long Documents

Reads markdown or plain text, splits intelligently into chunks, and streams to speakers or renders to file.

Usage:

kokoro-tts-tool infinite [OPTIONS]

Options:

• --input, -i PATH: Input text/markdown file
• --stdin, -s: Read text from stdin
• --output, -o PATH: Save to WAV file (fast offline mode)
• --voice VALUE: Voice ID (default: af_heart)
• --speed FLOAT: Speech speed 0.5-2.0 (default: 1.0)
• --chunk-size INT: Target words per chunk 50-1000 (default: 200)
• --pause INT: Pause between chunks in ms 0-2000 (default: 150)
• --no-markdown: Treat input as plain text

Examples:

# Stream to speakers
kokoro-tts-tool infinite --input book.md

# Render to WAV (fast, ~2-3min for 1hr audio)
kokoro-tts-tool infinite --input book.md --output audiobook.wav

# Pipe from stdin
cat chapter.md | kokoro-tts-tool infinite --stdin

# With custom voice and speed
kokoro-tts-tool infinite --input notes.md \
    --voice am_adam \
    --speed 1.2

# Render audiobook with narrator voice
kokoro-tts-tool infinite --input book.md \
    --output book.wav \
    --voice bm_george \
    --speed 0.95

# Shorter chunks for studying
kokoro-tts-tool infinite --input study.md \
    --chunk-size 200 \
    --pause 600

Output:

• Speaker mode: Real-time playback, seamless audio
• File mode: Fast offline rendering (20-50x real-time on M4)

---

list-voices - List Available Voices

Lists voice information including ID, name, gender, accent, quality grade, and description.

Usage:

kokoro-tts-tool list-voices [OPTIONS]

Options:

• --language, -l VALUE: Filter by language (English, Japanese, etc.)
• --gender, -g VALUE: Filter by gender (Male, Female)
• --json: Output as JSON for scripting

Examples:

# List all voices
kokoro-tts-tool list-voices

# Filter by language
kokoro-tts-tool list-voices --language English

# Filter by gender
kokoro-tts-tool list-voices --gender Female

# Combined filters
kokoro-tts-tool list-voices --language English --gender Male

# JSON output for scripting
kokoro-tts-tool list-voices --json

Voice ID Format:

• Pattern: [language][gender]_[name]
• First letter: language (a=American, b=British, j=Japanese, etc.)
• Second letter: gender (f=Female, m=Male)

Quality Grades:

• A/A-: Highest quality (af_heart, af_bella, am_adam)
• B+/B: Good quality
• B-: Acceptable quality

---

info - Display Configuration

Shows information about the Kokoro TTS installation.

Usage:

kokoro-tts-tool info

Examples:

kokoro-tts-tool info

Output:

• Model status (Ready/Not downloaded)
• Model file locations
• Default settings
• Supported languages

---

completion - Shell Completion

Generate shell completion scripts for bash, zsh, or fish.

Usage:

kokoro-tts-tool completion SHELL

Arguments:

• SHELL: Shell type (bash, zsh, fish)

Examples:

# Bash (add to ~/.bashrc)
eval "$(kokoro-tts-tool completion bash)"

# Zsh (add to ~/.zshrc)
eval "$(kokoro-tts-tool completion zsh)"

# Fish
kokoro-tts-tool completion fish > ~/.config/fish/completions/kokoro-tts-tool.fish

⚙️ Advanced Features (Click to expand)

Multi-Level Verbosity Logging

Control logging detail with progressive verbosity levels. All logs output to stderr.

Logging Levels:

Flag	Level	Output	Use Case
(none)	WARNING	Errors and warnings only	Production, quiet mode
-v	INFO	+ High-level operations	Normal debugging
-vv	DEBUG	+ Detailed info, full tracebacks	Development
-vvv	TRACE	+ Library internals	Deep debugging

Examples:

# INFO level
kokoro-tts-tool -v synthesize "Hello"

# DEBUG level
kokoro-tts-tool -vv infinite --input book.md

# TRACE level
kokoro-tts-tool -vvv synthesize "Hello"

---

Pipeline Composition

Compose commands with Unix pipes for workflows.

Examples:

# Get voice IDs as JSON and filter
kokoro-tts-tool list-voices --json | jq '.[].id'

# Read from another command
cat document.md | kokoro-tts-tool infinite --stdin

# Chain with file processing
find . -name "*.md" -exec cat {} \; | kokoro-tts-tool infinite --stdin

🔧 Troubleshooting (Click to expand)

Common Issues

Issue: Command not found

# Verify installation
kokoro-tts-tool --version

# Reinstall if needed
cd kokoro-tts-tool
uv tool install . --reinstall

Issue: Models not downloaded

# Initialize models
kokoro-tts-tool init

# Force re-download
kokoro-tts-tool init --force

Issue: Audio not playing

• Check system volume
• Try saving to file: --output test.wav
• Check with verbose: -vv

Issue: Voice not found

# List available voices
kokoro-tts-tool list-voices

# Check voice ID format
kokoro-tts-tool list-voices --json | jq '.[].id'

Getting Help

# General help
kokoro-tts-tool --help

# Command-specific help
kokoro-tts-tool synthesize --help
kokoro-tts-tool infinite --help

Exit Codes

• 0: Success
• 1: Error (validation, runtime, or unexpected)

Output Formats

Default Output:

• Human-readable formatted output
• Audio played through speakers

File Output (--output):

• WAV format (24kHz, mono, 16-bit)

JSON Output (--json on list-voices):

• Machine-readable voice data
• Perfect for pipelines and processing

Best Practices

1. Initialize first: Run kokoro-tts-tool init before synthesis
2. Use appropriate voices: Match voice to content (am_adam for audiobooks, bf_emma for education)
3. Leverage infinite for documents: Better than synthesize for long content
4. Use file output for production: --output for consistent results
5. Check voice quality grades: A/A- voices recommended for production

Resources

• GitHub: https://github.com/dnvriend/kokoro-tts-tool
• Kokoro-82M Model: https://huggingface.co/hexgrad/Kokoro-82M
• kokoro-onnx: https://github.com/thewh1teagle/kokoro-onnx