read-aloud_skill

This skill generates a standalone HTML reader from markdown with Kokoro TTS audio and word-synced highlighting for easy listening and proofreading.
  • Python

20

GitHub Stars

5

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill leegonzales/aiskills --skill read-aloud

  • CHANGELOG.md778 B
  • LICENSE1.0 KB
  • README.md3.6 KB
  • requirements.txt69 B
  • SKILL.md2.9 KB

Overview

This skill generates a standalone HTML reader with Kokoro TTS audio and word-synced highlighting from any markdown file. It produces a single self-contained reader.html that embeds compressed audio and real-time word highlighting for listening, proofreading, or sharing. The tool runs locally and outputs a pure static file you can open in any browser.

How this skill works

The pipeline creates per-paragraph WAV chunks with Kokoro TTS, transcribes each chunk with Whisper to get drift-free word timestamps, and then assembles a single HTML file embedding an MP3 and synchronized per-word timing. The reader includes playback controls, keyboard shortcuts, and click-to-seek behavior so users can jump to any word. A small wrapper script auto-creates a virtual environment and installs dependencies on first run.

When to use it

  • You want to listen to a markdown essay, article, or notes with synced highlighting.
  • You need to proofread by ear to catch rhythm, tone, or awkward phrasing.
  • You want a shareable, serverless audio reader (single HTML file) to distribute.
  • You prefer generating lightweight, offline audio readers for accessibility testing.
  • You need to convert chapters or sections into per-word-synced playback for review.

Best practices

  • Run on a macOS machine with Apple Silicon (M1+) for best compatibility and performance.
  • Use Python 3.13+ and install ffmpeg to produce compressed MP3 output.
  • Keep paragraphs reasonably sized to improve alignment accuracy during transcription.
  • Adjust --speed and --voice to match desired tone before generating the final reader.
  • Use --strip-sections to exclude non-narrative headings (e.g., References) to shorten audio.

Example use cases

  • Generate an audio reader for a long-form essay to proofread pacing and clarity by ear.
  • Create an offline HTML reader to share a narrated version of documentation or tutorials.
  • Produce a highlighted playback for accessibility reviews or user testing sessions.
  • Export chapter previews from markdown files to embed in a portfolio or preview page.
  • Quickly generate narrated drafts to evaluate voice, speed, and emphasis choices.

FAQ

The tool is designed for macOS on Apple Silicon and requires Python 3.13+. Other platforms may not be supported.

How long does generation take?

Typical essays take about 2–5 minutes; time depends on length and system performance.

Can I change voice or speed?

Yes. Use the --voice and --speed flags to pick a Kokoro voice variant and speech rate.

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