Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/lovstudio/skills/video-chapternpx skills add lovstudio/skills --skill video-chaptergit clone --depth 1 https://github.com/lovstudio/skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lovstudio/skills/video-chapter)<a href="https://agentmods.dev/skills/lovstudio/skills/video-chapter"><img src="https://agentmods.dev/badge/skills/lovstudio/skills/video-chapter.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00108 | $0.01226 |
| Opus 5 | $0.00054 | $0.00613 |
| Sonnet 5 | $0.00022 | $0.00245 |
| Haiku 4.5 | $0.00011 | $0.00123 |
Grade A, and why
lov-video-chapter scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.mdfor subtitle analysis and editorial cuts. - Read
skills/chapter-design/SKILL.mdfor React Studio editing and styling. - Read
skills/chapter-render/SKILL.mdfor transparent overlay or burned video. - Read
skills/chapter-export/SKILL.mdfor 剪映/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"
What ships with it
34 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .gitignore 91 B
- agents/openai.yaml 447 B
- assets/lov-video-chapter.svg 643 B
- CHANGELOG.md 995 B
- examples/demo-chapters.txt 320 B
- LICENSE 1.0 KB
- README.md 3.9 KB
- references/project-format.md 1.5 KB
- references/user-config.md 1.6 KB
- requirements.txt 13 B
- schemas/chapter-project.schema.json 3.1 KB
- scripts/chapter_project.py 14 KB runs code
- scripts/render_chapter_bar.py 16 KB runs code
- scripts/subtitle_chapters.py 11 KB runs code
- skill.yaml 840 B
- skills/chapter-design/SKILL.md 1.6 KB
- skills/chapter-export/SKILL.md 1.5 KB
- skills/chapter-plan/SKILL.md 1.7 KB
- skills/chapter-render/SKILL.md 1.4 KB
- studio/index.html 446 B
- studio/package.json 456 B
- studio/public/lov-video-chapter.svg 643 B
- studio/src/App.tsx 23 KB
- studio/src/ChapterOverlay.tsx 3.0 KB
- studio/src/defaultProject.ts 1.7 KB runs code
- studio/src/main.tsx 229 B
- studio/src/styles.css 18 KB
- studio/src/time.ts 1.0 KB runs code
- studio/src/types.ts 836 B runs code
- studio/src/vite-env.d.ts 38 B runs code
- studio/tsconfig.app.json 639 B
- studio/tsconfig.json 116 B
- studio/tsconfig.node.json 474 B
- studio/vite.config.ts 135 B runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 146 lines · 108 tokens per session scan A 1339113a0a7c
lov-video-chapter is a skill published in the GitHub repository lovstudio/skills (64 stars, last pushed 2d ago), licensed MIT. It adds 108 tokens to every session and 1,226 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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