edge-tts

High-quality neural text-to-speech audio generation with Microsoft Edge voices.

aahl/skillsUpdated Jun 12, 2026

Works with

Claude CodeCursorClineWindsurfCodexGooseGitHub CopilotZed

15

total installs

15

this week

111

GitHub stars

0

upvotes

Install Skill

Run in your terminal

$npx skills add https://github.com/aahl/skills --skill edge-tts

15

installs

15

this week

111

stars

What it does

  • Supports 30+ voices across English, French, and Chinese with adjustable speed, pitch, and volume

  • Generates MP3 audio files and optional WebVTT subtitles from plain text input

  • Triggered by \"tts\" keyword or when audio output is needed for accessibility, multitasking, or specific voice requirements

  • Command-line interface via uvx edge-tts with voice selection, rate/pitch/volume modulation, and subtitle o

Category

Productivity

Repository

aahl/skills

Last updated

Jun 12, 2026

Installation Guide

How to use edge-tts 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 machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add edge-tts
2

Run the install command

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

$npx skills add https://github.com/aahl/skills --skill edge-tts

Fetches edge-tts from aahl/skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/edge-tts

Restart Cursor to activate edge-tts. Access via /edge-tts in your agent's command palette.

Security 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 environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

Edge-TTS

Generate high-quality text-to-speech audio using Microsoft Edge's neural TTS service via the uvx edge-tts command. Supports multiple languages, voices, adjustable speed/pitch, and subtitle generation.

Usage

uvx edge-tts --text "{msg}" --write-media {tempdir}/{filename}.mp3

# With subtitles
uvx edge-tts --text "{msg}" --write-media {tempdir}/{filename}.mp3 --write-subtitles -

Changing rate(speed), volume and pitch

uvx edge-tts --text "{msg}" --write-media {tempdir}/{filename}.mp3 --rate=+50%
uvx edge-tts --text "{msg}" --write-media {tempdir}/{filename}.mp3 --volume=+50% --pitch=-50Hz

Changing the voice

uvx edge-tts --text "{msg}" --write-media {tempdir}/{filename}.mp3 --voice zh-CN-XiaoxiaoNeural

Available voices

Name                               Gender    ContentCategories      VoicePersonalities
en-GB-LibbyNeural                  Female    General                Friendly, Positive
en-GB-RyanNeural                   Male      General                Friendly, Positive
en-GB-SoniaNeural                  Female    General                Friendly, Positive
en-GB-ThomasNeural                 Male      General                Friendly, Positive
en-HK-SamNeural                    Male      General                Friendly, Positive
en-HK-YanNeural                    Female    General                Friendly, Positive
en-US-AnaNeural                    Female    Cartoon, Conversation  Cute
en-US-AndrewMultilingualNeural     Male      Conversation, Copilot  Warm, Confident, Authentic, Honest
en-US-AndrewNeural                 Male      Conversation, Copilot  Warm, Confident, Authentic, Honest
en-US-AriaNeural                   Female    News, Novel            Positive, Confident
en-US-AvaMultilingualNeural        Female    Conversation, Copilot  Expressive, Caring, Pleasant, Friendly
en-US-AvaNeural                    Female    Conversation, Copilot  Expressive, Caring, Pleasant, Friendly
en-US-BrianMultilingualNeural      Male      Conversation, Copilot  Approachable, Casual, Sincere
en-US-BrianNeural                  Male      Conversation, Copilot  Approachable, Casual, Sincere
en-US-ChristopherNeural            Male      News, Novel            Reliable, Authority
en-US-EmmaMultilingualNeural       Female    Conversation, Copilot  Cheerful, Clear, Conversational
en-US-EmmaNeural                   Female    Conversation, Copilot  Cheerful, Clear, Conversational
en-US-EricNeural                   Male      News, Novel            Rational
en-US-GuyNeural                    Male      News, Novel            Passion
en-US-JennyNeural                  Female    General                Friendly, Considerate, Comfort
en-US-MichelleNeural               Female    News, Novel            Friendly, Pleasant
en-US-RogerNeural                  Male      News, Novel            Lively
en-US-SteffanNeural                Male      News, Novel            Rational
fr-FR-DeniseNeural                 Female    General                Friendly, Positive
fr-FR-HenriNeural                  Male      General                Friendly, Positive
zh-CN-XiaoxiaoNeural               Female    News, Novel            Warm
zh-CN-YunjianNeural                Male      Sports,  Novel         Passion
zh-CN-liaoning-XiaobeiNeural       Female    Dialect                Humorous
zh-CN-shaanxi-XiaoniNeural         Female    Dialect                Bright
zh-HK-HiuGaaiNeural                Female    General                Friendly, Positive
zh-HK-WanLungNeural                Male      General                Friendly, Positive
zh-TW-HsiaoChenNeural              Female    General                Friendly, Positive
zh-TW-YunJheNeural                 Male      General                Friendly, Positive

Retrieve all available voices using shell commands:

uvx edge-tts --list-voices

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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

Steps

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

Related Skills

Reviews

4.527 reviews
  • D
    Diya PatelDec 24, 2024

    Registry listing for edge-tts matched our evaluation — installs cleanly and behaves as described in the markdown.

  • C
    Chaitanya PatilDec 20, 2024

    edge-tts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • A
    Ama LiuDec 20, 2024

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

  • J
    James HaddadNov 15, 2024

    edge-tts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • P
    Piyush GNov 11, 2024

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

  • A
    Ama SharmaNov 11, 2024

    edge-tts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • J
    James YangOct 6, 2024

    edge-tts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • S
    Shikha MishraOct 2, 2024

    Registry listing for edge-tts matched our evaluation — installs cleanly and behaves as described in the markdown.

  • K
    Kwame LiOct 2, 2024

    edge-tts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • A
    Aanya IyerSep 13, 2024

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

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