SuperAPI AI Directory

lovstudio-video-chapter

Design & creation

View repository

Updated 10-16 00:01

About this skill

Video Chapter Skill Kit

Build a complete chapter-bar workflow from semantic planning to final video. Keep every stage connected through one chapter-project.json.

Route the request

  • Read skills/chapter-plan/SKILL.md for subtitle analysis and editorial cuts.
  • Read skills/chapter-design/SKILL.md for React Studio editing and styling.
  • Read skills/chapter-render/SKILL.md for transparent overlay or burned video.
  • Read skills/chapter-export/SKILL.md for Jianying/CapCut and other editor packages.
  • Run only the stages the user requests. Run all four for an end-to-end request.

End-to-end workflow

1. Analyze the subtitles

python3 scripts/subtitle_chapters.py \
  --input "/path/to/subtitles.srt" \
  --segments 5 \
  --output "/tmp/video-chapter-analysis.md"

Read the analysis pack completely. Select semantic transitions rather than equal-duration cuts. Start at 00:00, align later cuts to subtitle cues, and avoid cutting a sentence.

2. Create the project

Write a UTF-8 chapter list:

00:00 开场与目标 | 展示成片并说明这次要完成什么
04:16 挑选并改造 Skill | 判断现有工具并完成适配

Create the canonical project:

python3 scripts/chapter_project.py create \
  --chapters "/path/to/chapters.txt" \
  --video "/path/to/video.mp4" \
  --output "/path/to/chapter-project.json"

Read references/project-format.md when editing project JSON directly.

3. Refine in React Studio

cd studio
npm install
npm run dev

Import chapter-project.json, select the local source video, edit chapter boundaries and titles, adjust styling, then export the updated JSON. Treat the Studio preview as the visual approval surface.

4. Render

Install Pillow once when needed:

python3 -m pip install -r requirements.txt

Create a transparent overlay:

python3 scripts/render_chapter_bar.py overlay \
  --project "/path/to/chapter-project.json" \
  --output "/path/to/chapter-overlay.mov"

Burn the overlay into the source video:

python3 scripts/render_chapter_bar.py burn \
  --project "/path/to/chapter-project.json" \
  --output "/path/to/video-with-chapters.mp4"

Create a Jianying-ready package:

python3 scripts/render_chapter_bar.py package \
  --project "/path/to/chapter-project.json" \
  --output "/path/to/chapter-package"

Validation

Run before delivery:

python3 scripts/chapter_project.py validate \
  --project "/path/to/chapter-project.json"

Confirm:

  • chapters are chronological and contiguous;
  • the final chapter ends at the project duration;
  • titles match the following content;
  • the Studio preview matches the requested visual direction;
  • the overlay contains an alpha channel;
  • the burned MP4 preserves source audio;
  • the editor package contains JSON, timestamps, CSV, overlay, and instructions.

Output policy

  • Prefer a transparent ProRes 4444 MOV for Jianying/CapCut.
  • Use burned MP4 when the user wants a final publishable file.
  • Describe transparent-video import as asset integration.
  • Keep editor-specific draft writers in an experimental adapter layer.
  • Preserve explicit paths; never assume a private workspace.