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 davidtoby/agent-skills --skill youtube-bilingual-transcript-reportgit clone --depth 1 https://github.com/davidtoby/agent-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/davidtoby/agent-skills/youtube-bilingual-transcript-report)<a href="https://agentmods.dev/skills/davidtoby/agent-skills/youtube-bilingual-transcript-report"><img src="https://agentmods.dev/badge/skills/davidtoby/agent-skills/youtube-bilingual-transcript-report/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/davidtoby/agent-skills/youtube-bilingual-transcript-report"><img src="https://agentmods.dev/badge/skills/davidtoby/agent-skills/youtube-bilingual-transcript-report.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 | $0.00057 | $0.01907 |
| Opus 5.5 | $0.00023 | $0.00763 |
| Sonnet 5.5 | $0.00011 | $0.00381 |
| Haiku 4.5 | $0.00006 | $0.00191 |
Grade A, and why
youtube-bilingual-transcript-report 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 1mo 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 — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube Bilingual Transcript Report
Use when the user gives a YouTube URL and wants:
- the video downloaded locally
- English and Chinese transcripts
- a structured summary
- original insights / commentary
- a polished PDF deliverable
This is a report workflow, not just a subtitle workflow.
Output standard
Save everything under:
~/.Hermes/workspace/output/<self-descriptive-task-folder>/
Preferred deliverables:
- source video (practical resolution if full quality is unnecessary)
- English structured transcript
- Chinese structured transcript
- summary + insights markdown
- final combined markdown report
- final PDF
Use self-descriptive filenames.
Proven workflow
1) Prepare task folder and inspect metadata
mkdir -p ~/.Hermes/workspace/output/<task-folder>
yt-dlp --dump-single-json --no-warnings '<youtube-url>' > video_info.json
yt-dlp --list-subs '<youtube-url>' > subs_list.txt 2>&1 || true
Capture at least:
- title
- uploader/channel
- duration
- upload date
2) Do not blindly download a massive source first
For transcript/report tasks, full-resolution download is often wasteful.
A real run encountered a 2.54 GB source that timed out and was unnecessary for PDF/report delivery.
Prefer a practical MP4 such as 360p unless the user explicitly needs high quality:
yt-dlp --no-playlist \
-f 'bv*[height<=360][ext=mp4]+ba[ext=m4a]/b[height<=360][ext=mp4]/b[height<=360]' \
-o '<descriptive-name>_[%(id)s].%(ext)s' \
'<youtube-url>'
Guideline:
- if the task is transcript/summary/PDF first, optimize for completion speed
- only fetch huge source media when downstream work truly needs it
3) Download English subtitle tracks first
Try English auto-captions first:
yt-dlp --skip-download --write-auto-sub --sub-langs 'en-orig,en' --sub-format srt \
-o '%(title).120s [%(id)s].%(ext)s' '<youtube-url>'
4) Chinese subtitle download may fail with HTTP 429
A real run had this exact failure even though --list-subs showed zh-Hans / zh-Hant tracks.
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.
- 1mo ago First seen · 257 lines · 57 tokens per session scan A 9399ba496842
youtube-bilingual-transcript-report is a skill published in the GitHub repository davidtoby/agent-skills (11 stars, last pushed 2mo ago), licensed MIT. It adds 57 tokens to every session and 1,907 once invoked, about $0.0002 per session on Opus 5.5. 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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