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 skills add jykim/claude-obsidian-skills --skill video-add-chaptersgit clone --depth 1 https://github.com/jykim/claude-obsidian-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/jykim/claude-obsidian-skills/video-add-chapters)<a href="https://agentmods.dev/skills/jykim/claude-obsidian-skills/video-add-chapters"><img src="https://agentmods.dev/badge/skills/jykim/claude-obsidian-skills/video-add-chapters/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jykim/claude-obsidian-skills/video-add-chapters"><img src="https://agentmods.dev/badge/skills/jykim/claude-obsidian-skills/video-add-chapters.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00032 | $0.02272 |
| Opus 5 | $0.00016 | $0.01136 |
| Sonnet 5 | $0.00006 | $0.00454 |
| Haiku 4.5 | $0.00003 | $0.00227 |
Grade A, and why
video-add-chapters 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 13d ago.
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 — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
video-add-chapters
Transcribe videos using Whisper API, automatically detect chapter boundaries, and generate structured markdown documents with YouTube chapter markers. Optionally create highlight videos from selected segments.
When to Use This Skill
- Transcribing long videos (20+ minutes) and splitting into chapters
- Converting video transcripts into structured documentation
- Generating YouTube chapter markers for video descriptions
- Cleaning up raw transcripts into readable documents
- Creating highlight videos from selected transcript segments
Example Results
- Live Example: AI4PKM W2 Tutorial Part 1
- See
examples/folder for sample outputs
Requirements
System
- Python 3.7+
- FFmpeg (for audio extraction)
Python Packages
pip install -r requirements.txt
Environment Variables
OPENAI_API_KEY- Required for Whisper API
How It Works
flowchart TB
subgraph Auto[Automatic Processing]
direction LR
A[Video] --> B[Transcribe] --> C[Analyze] --> D[Generate] --> E[Clean]
end
subgraph Optional[Optional Review]
F[Check & Adjust]
end
Auto -.-> Optional -.-> Auto
All steps run automatically without user intervention. Optional review step available if manual adjustment is needed.
Usage
Quick Start (Automated Pipeline)
# Run all steps automatically
python transcribe_video.py "video.mp4" --language ko --output-dir "./output"
python suggest_chapters.py "video.mp4" --output "chapters.json"
python generate_docs.py "video.mp4" --chapters "chapters.json" --output-dir "./output"
python clean_transcript.py "./output/merged_document.md" --backup
Step-by-Step Details
1. Transcribe Video
python transcribe_video.py "video.mp4" --language ko --output-dir "./output"
# Skip if transcript already exists (useful for workflow integration)
python transcribe_video.py "video.mp4" --skip-if-exists
- Splits video into 15-minute chunks
- Transcribes using Whisper API
- Handles timestamp offsets automatically
- Output:
{video} - transcript.json
What ships with it
13 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.
- clean_transcript.py 8.3 KB runs code
- examples/sample_chapter.md 1.1 KB
- examples/sample_youtube_chapters.txt 543 B
- export_highlight_script.py 4.6 KB runs code
- generate_docs.py 10 KB runs code
- generate_highlights.py 7.5 KB runs code
- parse_highlight_annotations.py 7.1 KB runs code
- requirements.txt 14 B
- suggest_chapters.py 8.6 KB runs code
- templates/chapter.md 532 B
- templates/index.md 475 B
- templates/youtube_chapters.txt 230 B
- transcribe_video.py 7.7 KB 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.
- 13d ago First seen · 304 lines · 32 tokens per session scan A 3c296be2e1df
video-add-chapters is a skill published in the GitHub repository jykim/claude-obsidian-skills (50 stars, last pushed 20d ago), licensed MIT. It adds 32 tokens to every session and 2,272 once invoked, about $0.0002 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 2026-08-30.
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