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 katalalab/katala-os --skill video-transcript-downloadergit clone --depth 1 https://github.com/katalalab/katala-osWrote 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/katalalab/katala-os/video-transcript-downloader)<a href="https://agentmods.dev/skills/katalalab/katala-os/video-transcript-downloader"><img src="https://agentmods.dev/badge/skills/katalalab/katala-os/video-transcript-downloader/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/katalalab/katala-os/video-transcript-downloader"><img src="https://agentmods.dev/badge/skills/katalalab/katala-os/video-transcript-downloader.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00051 | $0.00443 |
| Opus 5 | $0.00026 | $0.00221 |
| Sonnet 5 | $0.00010 | $0.00089 |
| Haiku 4.5 | $0.00005 | $0.00044 |
Grade A, and why
video-transcript-downloader 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 10d 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.
What it actually says
video-transcript-downloader — video transcript extraction
Downloads auto-generated or manual subtitles and converts them to clean Markdown.
When to use
- "この YouTube 動画の文字起こしが欲しい"
- "この動画の内容をテキストにして"
- "transcript をダウンロードして要約したい"
Do not use for:
- Downloading audio or video files (use yt-dlp directly)
- Videos with no available subtitles (will fail gracefully)
- Paid/paywalled content
Extraction steps
# 1. Check available subtitles
yt-dlp --list-subs "<url>"
# 2. Download preferred subtitles (Japanese first, English fallback)
yt-dlp --write-subs --write-auto-subs --sub-lang "ja,en" \
--skip-download --convert-subs srt \
-o "%(title)s.%(ext)s" "<url>"
# 3. Convert SRT to clean Markdown (strip timestamps)
python3 - <<'EOF'
import re, sys
srt = open(sys.argv[1]).read()
lines = re.sub(r'\d+\n\d{2}:\d{2}:\d{2},\d{3} --> \d{2}:\d{2}:\d{2},\d{3}\n', '', srt)
lines = re.sub(r'\n{3,}', '\n\n', lines).strip()
print(lines)
EOF transcript.srt > transcript.md
Output
Clean Markdown file at ~/work/docs/transcripts/<video-title>.md or operator-specified path.
Hard-rule reminders
- Only download from publicly accessible URLs.
- Check license/terms before using transcript content commercially.
- yt-dlp must be installed:
brew install yt-dlp.
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.
- 10d ago First seen · 51 lines · 51 tokens per session scan A a90c4013a9c6
video-transcript-downloader is a skill published in the GitHub repository katalalab/katala-os (2 stars, last pushed 11d ago), licensed MIT. It adds 51 tokens to every session and 443 once invoked, about $0.0003 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 2026-08-31.
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