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 jscholz/hermes-agent-workflow --skill youtube-contentgit clone --depth 1 https://github.com/jscholz/hermes-agent-workflowWrote 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/jscholz/hermes-agent-workflow/youtube-content)<a href="https://agentmods.dev/skills/jscholz/hermes-agent-workflow/youtube-content"><img src="https://agentmods.dev/badge/skills/jscholz/hermes-agent-workflow/youtube-content/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/jscholz/hermes-agent-workflow/youtube-content"><img src="https://agentmods.dev/badge/skills/jscholz/hermes-agent-workflow/youtube-content.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 | $0.00062 | $0.00708 |
| Opus 5 | $0.00031 | $0.00354 |
| Sonnet 5 | $0.00012 | $0.00142 |
| Haiku 4.5 | $0.00006 | $0.00071 |
Grade A, and why
youtube-content 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 8d 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.
This is a copy
91% identical to youtube-content — 35 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube Content Tool
Extract transcripts from YouTube videos and convert them into useful formats.
Setup
pip install youtube-transcript-api
Helper Script
SKILL_DIR is the directory containing this SKILL.md file. The script accepts any standard YouTube URL format, short links (youtu.be), shorts, embeds, live links, or a raw 11-character video ID.
# JSON output with metadata
python3 SKILL_DIR/scripts/fetch_transcript.py "https://youtube.com/watch?v=VIDEO_ID"
# Plain text (good for piping into further processing)
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --text-only
# With timestamps
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --timestamps
# Specific language with fallback chain
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --language tr,en
Output Formats
After fetching the transcript, format it based on what the user asks for:
- Chapters: Group by topic shifts, output timestamped chapter list
- Summary: Concise 5-10 sentence overview of the entire video
- Chapter summaries: Chapters with a short paragraph summary for each
- Thread: Twitter/X thread format — numbered posts, each under 280 chars
- Blog post: Full article with title, sections, and key takeaways
- Quotes: Notable quotes with timestamps
Example — Chapters Output
00:00 Introduction — host opens with the problem statement
03:45 Background — prior work and why existing solutions fall short
12:20 Core method — walkthrough of the proposed approach
24:10 Results — benchmark comparisons and key takeaways
31:55 Q&A — audience questions on scalability and next steps
Workflow
- Fetch the transcript using the helper script with
--text-only --timestamps. - Validate: confirm the output is non-empty and in the expected language. If empty, retry without
--languageto get any available transcript. If still empty, tell the user the video likely has transcripts disabled. - Chunk if needed: if the transcript exceeds ~50K characters, split into overlapping chunks (~40K with 2K overlap) and summarize each chunk before merging.
- Transform into the requested output format. If the user did not specify a format, default to a summary.
- Verify: re-read the transformed output to check for coherence, correct timestamps, and completeness before presenting.
What ships with it
2 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.
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.
- 8d ago First seen · 73 lines · 62 tokens per session scan A 121d625bacad
youtube-content is a skill published in the GitHub repository jscholz/hermes-agent-workflow (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 62 tokens to every session and 708 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to youtube-content, differing in 35 lines, and is treated as a copy.
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