text-to-speech

heygen-com/skills · updated Jun 4, 2026

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$npx skills add https://github.com/heygen-com/skills --skill text-to-speech
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summary

Generate speech audio from text using HeyGen's Starfish TTS model with voice, speed, and pitch control.

  • List available TTS voices by language and gender, then generate audio files with customizable speed (0.5–1.5) and pitch (−50 to 50)
  • Supports multilingual voices with locale selection (e.g., pt-BR ) and SSML-style break tags for pauses within text
  • Returns audio URL, duration, request ID, and word-level timestamps for caption syncing or timed overlays
  • Requires HEYGEN_API_KEY envir
skill.md

Text-to-Speech (HeyGen Starfish)

Generate speech audio files from text using HeyGen's in-house Starfish TTS model via the v3 API. This skill is for standalone audio generation — separate from video creation.

Authentication

All requests require the X-Api-Key header. Set the HEYGEN_API_KEY environment variable.

curl -X GET "https://api.heygen.com/v3/voices?engine=starfish" \
  -H "X-Api-Key: $HEYGEN_API_KEY"

Tool Selection

If HeyGen MCP tools are available (mcp__heygen__*), prefer them over direct HTTP API calls.

Task MCP Tool Fallback (Direct API)
List TTS voices mcp__heygen__list_audio_voices GET /v3/voices?engine=starfish
Generate speech audio mcp__heygen__text_to_speech POST /v3/voices/speech

Default Workflow

  1. List voices with mcp__heygen__list_audio_voices (or GET /v3/voices?engine=starfish)
  2. Pick a voice matching desired language, gender, and features
  3. Call mcp__heygen__text_to_speech (or POST /v3/voices/speech) with text and voice_id
  4. Use the returned audio_url to download or play the audio

List TTS Voices

Retrieve voices compatible with the Starfish TTS model.

Note: This uses the unified GET /v3/voices endpoint with the engine=starfish filter to return only TTS-compatible voices. Not all video voices support Starfish TTS. The response is paginated — use next_token to fetch additional pages.

Query Parameters

Param Type Description
engine string Filter by engine (use starfish for TTS voices)
type string public or private
language string Filter by language
gender string Filter by gender
limit integer Results per page, 1-100
token string Pagination cursor from next_token

curl

curl -X GET "https://api.heygen.com/v3/voices?engine=starfish" \
  -H "X-Api-Key: $HEYGEN_API_KEY"

TypeScript

interface AudioVoiceItem {
  voice_id: string;
  name: string;
  language: string;
  gender: "female" | "male" | "unknown";
  preview_audio_url: string | null;
  support_pause: boolean;
  support_locale: boolean;
  type: string;
}

interface TTSVoicesResponse {
  error: null | string;
  data: AudioVoiceItem[];
  has_more: boolean;
  next_token: string | null;
}

async function listTTSVoices(): Promise<AudioVoiceItem[]> {
  const allVoices: AudioVoiceItem[] = [];
  let token: string | null = null;

  do {
    const url = new URL("https://api.heygen.com/v3/voices");
    url.searchParams.set("engine", "starfish");
    if (token) url.searchParams.set("token", token);

    const response = await fetch(url.toString(), {
      headers: { "X-Api-Key": process.env.HEYGEN_API_KEY! },
    });

    const json: TTSVoicesResponse = await response.json();

    if (json.error) {
      throw new Error(json.error);
    }

    allVoices.push(...json.data);
    token = json.next_token;
  } while (token);

  return allVoices;
}

Python

import requests
import os

def list_tts_voices() -> list:
    all_voices = []
    token = None

    while True:
        params = {"engine": "starfish"}
        if token:
            params["token"] = token

        response = requests.get(
            "https://api.heygen.com/v3/voices",
            headers={"X-Api-Key": os.environ["HEYGEN_API_KEY"]},
            params=params,
        )

        data = response.json()
        if data.get("error"):
            raise Exception(data["error"])

        all_voices.extend(data["data"])

        if not data.get("has_more"):
            break
        token = data.get("next_token")

    return all_voices

Response Format

{
  "error": null,
  "data": [
    {
      "voice_id": "f38a635bee7a4d1f9b0a654a31d050d2",
      "name": "Chill Brian",
      "language": "English",
      "gender": "male",
      "preview_audio_url": "https://resource.heygen.ai/text_to_speech/WpSDQvmLGXEqXZVZQiVeg6.mp3",
      "support_pause": true,
      "support_locale": false,
      "type": "public"
    }
  ],
  "has_more": false,
  "next_token": null
}

Generate Speech Audio

Convert text to speech audio using a specified voice.

Endpoint

POST https://api.heygen.com/v3/voices/speech

Request Fields

Field Type Req Description
text string Y Text content to convert (1-5000 characters)
voice_id string Y Voice ID from GET /v3/voices?engine=starfish
input_type string "text" (default) or "ssml" for full SSML markup
speed number Speech speed, 0.5-2.0 (default: 1.0)
language string Base language code (e.g., "en", "pt"). Auto-detected if omitted
locale string BCP-47 locale for multilingual voices (e.g., "en-US", "pt-BR")

curl

curl -X POST "https://api.heygen.com/v3/voices/speech" \
  -H "X-Api-Key: $HEYGEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "text": "Hello! Welcome to our product demo.",
    "voice_id": "YOUR_VOICE_ID",
    "speed": 1.0
  }'

TypeScript

interface TTSRequest {
  text: string;
  voice_id: string;
  input_type?: "text" | "ssml";
  speed?: number;
  language
how to use text-to-speech

How to use text-to-speech on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add text-to-speech
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/heygen-com/skills --skill text-to-speech

The skills CLI fetches text-to-speech from GitHub repository heygen-com/skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/text-to-speech

Reload or restart Cursor to activate text-to-speech. Access the skill through slash commands (e.g., /text-to-speech) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.551 reviews
  • Yuki Martin· Dec 28, 2024

    text-to-speech reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ren Kim· Dec 20, 2024

    Keeps context tight: text-to-speech is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Yuki Dixit· Dec 8, 2024

    We added text-to-speech from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • William Mensah· Nov 27, 2024

    Solid pick for teams standardizing on skills: text-to-speech is focused, and the summary matches what you get after install.

  • Luis Chen· Nov 19, 2024

    text-to-speech is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ren Mehta· Nov 15, 2024

    text-to-speech reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Arya Ndlovu· Nov 11, 2024

    Registry listing for text-to-speech matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Sakshi Patil· Nov 7, 2024

    I recommend text-to-speech for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Chaitanya Patil· Oct 26, 2024

    Useful defaults in text-to-speech — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Yuki Kapoor· Oct 18, 2024

    text-to-speech has been reliable in day-to-day use. Documentation quality is above average for community skills.

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