tts

Integrate neural TTS models across Rust, Python, and TypeScript.

3|Updated Jan 10, 2026
One-click install
npx skills add https://github.com/yankeeinlondon/rusty-biscuit --skill tts-yankeeinlondon
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: tts
Source: https://github.com/yankeeinlondon/rusty-biscuit/tree/main/.claude/skills/tts
Command: npx skills add https://github.com/yankeeinlondon/rusty-biscuit --skill tts-yankeeinlondon

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Text-to-Speech (TTS) skill provides a comprehensive framework to design, compare, and implement sophisticated speech synthesis workflows across local and cloud providers, covering models, languages, and control standards.

Core Features & Use Cases

  • Unified access to neural TTS models (Kokoro, Piper, ElevenLabs, OpenAI), language bindings for Rust, Python, and TypeScript, SSML and LLM-TTS voice control standards, and CLI tooling for deployment.
  • Voice cloning, offline/local deployment, and cloud/offline tradeoffs with guidance on latency, privacy, and cost considerations.
  • Real-world scenarios include building voice assistants, multi-language narrators, and accessible content with precise prosody control.

Quick Start

Synthesize a sample sentence using a selected model and voice to validate the end-to-end TTS integration.

Frequently Asked Questions about tts

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate text-to-speech models like Kokoro and Piper into a Python or Rust application?

To integrate text-to-speech models, use the provided language bindings for Rust, Python, and TypeScript to connect neural TTS providers like Kokoro and Piper into your application workflow for local or cloud speech synthesis.

What is the best way to choose between cloud TTS providers and offline voice cloning for production?

Choosing between cloud TTS providers and offline voice cloning requires evaluating tradeoffs in latency, privacy, and cost, using guidance on cloud and offline deployment options to meet production-grade speech synthesis needs.

Does this TTS skill support SSML and LLM-TTS voice control standards for prosody adjustment?

Yes, this TTS skill supports SSML and LLM-TTS voice control standards, enabling precise prosody control for building voice assistants, multi-language narrators, and accessible content with neural speech synthesis.

Can I deploy neural speech synthesis models locally using CLI tooling?

Yes, you can deploy neural speech synthesis models locally using the included CLI tooling, which supports offline deployment and configuration for providers like Kokoro and Piper without requiring external cloud APIs.

How do I build a multi-language narrator using ElevenLabs and OpenAI voice synthesis APIs?

Building a multi-language narrator involves leveraging unified access to ElevenLabs and OpenAI APIs, applying SSML standards for language-specific prosody control to generate accessible content across different languages.

What are the limitations of using local TTS deployment versus cloud speech synthesis?

Local TTS deployment limitations involve managing computational overhead and latency tradeoffs, whereas cloud speech synthesis shifts resource burdens but introduces privacy considerations and API latency dependencies.