faceless-explainer

Generates faceless explainer videos from arbitrary text via TTS narration and scripted HTML scenes.

Updated Jun 20, 2026
One-click install
npx skills add https://github.com/Noetfield-Systems/SourceA --skill faceless-explainer-noetfield-systems
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: faceless-explainer
Source: https://github.com/Noetfield-Systems/SourceA/tree/main/commercial-video-factory/trustfield-storyboard-hf-v1/.agents/skills/faceless-explainer
Command: npx skills add https://github.com/Noetfield-Systems/SourceA --skill faceless-explainer-noetfield-systems

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires puppeteer-core, elevenlabs, transformers, torch, soundfile, numpy, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve? Turning an article, notes, or a topic brief into a narrated explainer video normally requires scripting, voiceover recording, motion design, and video assembly. This Skill automates that entire pipeline: it converts arbitrary text into a narrator script, synthesizes voiceover and background music, designs typography/abstract/diagram/data-viz scenes, and renders a finished video up to about 3 minutes long. ## Core Features & Use Cases - Text-to-video orchestration: A binding multi-phase runbook (init, scaffold, scriptwriting, design system, audio, visual design, captions, parallel scene workers, finalize) that produces narrator_scripts.json, audio_meta.json, section_plan.md, group_spec.json, and a rendered video.mp4. - Generated narration and music: TTS via HeyGen, ElevenLabs, or local Kokoro, plus BGM via Lyria or local MusicGen, with word-level timestamps driving deterministic captions. - Auto-selected visual style: The scriptwriting agent picks one of five shipped style presets (block-frame, capsule, claude, pin-and-paper, scatterbrain) and landscape/portrait/square orientation per input. - Use Case: Paste a blog post about a technical concept and receive a 60-90 second captioned explainer video with synthesized narration, background music, and animated typography scenes, with no website capture or product screenshots involved. ## Quick Start Ask the agent to turn your article or notes into a faceless explainer video, then confirm the topic, length, aspect ratio, and language when prompted.

Frequently Asked Questions about faceless-explainer

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

FAQPage Schema
How do I turn an article into an explainer video?

Provide the article text and confirm the topic, length, aspect ratio, and language when prompted. The pipeline writes a narrator script, synthesizes voice and background music, designs typography or diagram scenes, and renders a finished video.mp4.

What text-to-speech providers does the video pipeline support?

TTS runs through HeyGen cloud with word-level timestamps, ElevenLabs with its Python SDK, or local Kokoro as a no-key fallback. Background music uses Lyria with a Gemini API key or local MusicGen via HuggingFace transformers.

Can I use my own pre-recorded voiceover with this workflow?

No, this workflow generates its own narration via TTS and does not sync visuals to a user-supplied or pre-recorded voiceover. For timing visuals to existing audio, the general-video workflow is the correct route.

What video lengths and aspect ratios are supported?

Typical output is up to about 3 minutes with a sweet spot of 30-90 seconds. Orientation is set at brief time: 16:9 landscape at 1920x1080, 9:16 portrait at 1080x1920, or 1:1 square at 1080x1080.

Why does the workflow refuse product marketing or website capture inputs?

This skill only explains topics with invented visuals and no captured assets. Text that markets a product or names its site routes to product-launch-video, and URLs route to website-to-video, keeping each pipeline's assumptions intact.

What are the system requirements for running the video pipeline?

It requires macOS Apple Silicon or Linux x64 with Homebrew Python 3.11, Node, and ffmpeg installed. Running npx hyperframes doctor once downloads the Chrome browser used by the rendered overlap gate and headless checks.