video-narration

name	video-narration
description	Generate narration for silent screen-recording videos. Extracts key frames, analyzes on-screen content, writes a presentation-style voiceover script, synthesizes natural-sounding speech with Microsoft Edge neural TTS, and merges the audio onto the original video. Outputs a narrated video and a companion voiceover script.
metadata	{"openclaw":{"emoji":"🎬","requires":{"anyBins":"[Truncated]"}}}

Video Narration Skill

You generate professional voiceover narration for silent screen-recording demo videos.

Workflow

1. Analyze the Video

Extract key frames and understand what is happening on screen:

# Extract one frame every 5 seconds
./scripts/extract-frames.sh <video_path> [output_dir]

• View every extracted frame to build a complete understanding.
• Identify the narrative arc: what is the setup, the action, the key moments, and the result.

2. Write the Voiceover Script

Write a presentation-style narration — not a dry description. Follow this structure:

Section	Purpose
Context	Tell the audience what they're about to see and why it matters
Background	Explain the setup / scenario
Prompt / Action	Show what the user actually did (keep it minimal)
Walkthrough	Narrate each major step, highlighting insights and turning points
Result	Land the payoff — what was found, what was fixed, why it's impressive

Guidelines:

• Use conversational, confident language — like presenting to peers.
• Use short punchy sentences for emphasis. Vary sentence length for rhythm.
• Highlight "aha moments" — the points where something surprising or clever happens.
• Name specific tools, commands, and values when they matter to the story.
• End with a memorable one-liner that captures the value.
• Total word count must fit the video duration (~2.5 words/second at normal pace).

Save the script as <video_name>_voiceover.md alongside the video.

3. Generate TTS Audio

Use the generate script to synthesize each narration segment:

./scripts/generate-tts.sh <script_sections_file> <output_dir> [voice] [rate]

Or generate directly via Python with edge-tts:

• Voice: en-US-GuyNeural (natural male) or en-US-AvaNeural (natural female)
• Rate: Adjust between +0% and +10% to fit the video duration
• Generate each section as a separate audio segment for precise timing control
• Concatenate segments with ~0.4s silence gaps between them
• Verify total duration matches the video (±2 seconds)

4. Merge Audio onto Video

./scripts/merge-audio.sh <video_path> <narration_audio> [output_path]

• Preserves the original video codec (copy, no re-encode)
• Encodes audio as AAC at 192kbps
• Uses -shortest to match the shorter of video/audio
• Verify the output has both video and audio streams

Timing Strategy

1. Generate all segments, measure each duration
2. Sum total speech time vs video duration
3. If speech is >105% of video: tighten the script or increase rate
4. If speech is <85% of video: the pacing may feel rushed — add detail or slow the rate
5. Concatenate with 0.3–0.5s gaps, target total within ±2s of video

Prerequisites

Install dependencies if not present:

pip3 install edge-tts   # Microsoft neural TTS (free, no API key)
brew install ffmpeg      # or apt-get install ffmpeg

Output

The skill produces:

1. <name> (with narration).mov — the video with baked-in voiceover
2. <name>_voiceover.md — the timestamped script for reference or re-recording