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/nicepkg/ai-workflow/youtube-processornpx skills add nicepkg/ai-workflow --skill youtube-processorgit clone --depth 1 https://github.com/nicepkg/ai-workflowWhat 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 | $0.00066 | $0.01379 |
| Opus 5 | $0.00033 | $0.00690 |
| Sonnet 5 | $0.00013 | $0.00276 |
| Haiku 4.5 | $0.00007 | $0.00138 |
Grade A, and why
youtube-processor 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 2d 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 — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube Processor
What This Does
Takes a YouTube URL, extracts the transcript, and you (Claude) summarize it. Outputs Obsidian-ready markdown. Zero friction: share a link, get actionable notes.
When to Use
- "Summarize this video: [URL]"
- "Turn this YouTube into notes"
- "What's this video about?"
- "Process this for my newsletter"
- Any YouTube URL shared for processing
Location
This skill's tools live at:
/Users/eddale/Documents/GitHub/powerhouse-lab/skills/youtube-processor/tools/
How It Works
Step 1: Python extracts the transcript (no API key needed) Step 2: You (Claude) summarize using your intelligence + context Step 3: You write the Obsidian-formatted output
This approach means you can use mission-context, newsletter-coach, and other skills during summarization.
Instructions
Which Method to Use
| Environment | Method |
|---|---|
| Claude Code | Local Python script (Step 1a) |
| Claude.ai / Mac Client | API via WebFetch (Step 1b) |
Step 1a: Extract Transcript (Claude Code)
Run the Python tool to get the transcript:
cd /Users/eddale/Documents/GitHub/powerhouse-lab/skills/youtube-processor/tools && \
python3 get_transcript.py --url "[URL]"
For JSON output (easier to parse):
python3 get_transcript.py --url "[URL]" --json
Step 1b: Extract Transcript (Claude.ai / Mac Client)
Use the API endpoint via WebFetch:
WebFetch: https://youtube-processor-eight.vercel.app/transcript?url=[VIDEO_URL]
The API returns JSON:
{
"success": true,
"video_id": "abc123",
"language": "en",
"transcript": "...",
"char_count": 5000,
"word_count": 850
}
Example prompt for WebFetch: "Extract the transcript text from the response"
Step 2: Summarize the Transcript
Once you have the transcript, summarize it based on what the user needs:
Quick Summary:
- Headline (1 sentence)
- Key points (3-5 bullets)
- Main takeaway
What ships with it
11 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.
- 2d ago First seen · 243 lines · 66 tokens per session scan A 1200461e69d8
youtube-processor is a skill published in the GitHub repository nicepkg/ai-workflow (282 stars, last pushed 7mo ago), licensed MIT. It adds 66 tokens to every session and 1,379 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 2026-08-30.
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