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 nikhilbhansali/youtube-data-skills --skill youtube-comment-minergit clone --depth 1 https://github.com/nikhilbhansali/youtube-data-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/nikhilbhansali/youtube-data-skills/youtube-comment-miner)<a href="https://agentmods.dev/skills/nikhilbhansali/youtube-data-skills/youtube-comment-miner"><img src="https://agentmods.dev/badge/skills/nikhilbhansali/youtube-data-skills/youtube-comment-miner/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/nikhilbhansali/youtube-data-skills/youtube-comment-miner"><img src="https://agentmods.dev/badge/skills/nikhilbhansali/youtube-data-skills/youtube-comment-miner.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 | $0.00119 | $0.01388 |
| Opus 5 | $0.00060 | $0.00694 |
| Sonnet 5 | $0.00024 | $0.00278 |
| Haiku 4.5 | $0.00012 | $0.00139 |
Grade A, and why
youtube-comment-miner 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 12d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube Comment Miner
Mine YouTube comments to extract content ideas, audience questions, pain points, and monetization signals.
Usage
/youtube-comment-miner https://youtube.com/watch?v=VIDEO_ID
/youtube-comment-miner @ChannelHandle --top 5
/youtube-comment-miner --topic "meditation for beginners" --top 10
/youtube-comment-miner VIDEO_ID1 VIDEO_ID2 VIDEO_ID3
Instructions
Step 1: Parse Arguments
Input mode (one of):
- Video URL(s) or ID(s): specific videos to mine
- Channel (
@handle, URL, or ID) +--top N: mine the channel's top N videos by views (default: 5) - Topic (
--topic "keyword") +--top N: search for videos on the topic, mine the top N (default: 10)
Also:
- --max-comments N (optional): max comments per video (default: 100, max: 500)
- --scan-limit N (optional, channel mode): cap how many uploads get scanned (default: whole channel)
Step 2: Get the API Key
Check the user's Claude memory for a YouTube Data API v3 key. If not found, ask:
"I need a YouTube Data API v3 key to mine comments. You can get one from the Google Cloud Console. Please paste your key."
Step 3: Run the Bundled Script
Run scripts/mine_comments.py — resolve the path relative to this skill's own directory:
# Specific videos
YT_API_KEY=API_KEY python3 <skill-dir>/scripts/mine_comments.py --videos VIDEO_ID1 VIDEO_ID2 --max-comments 100
# Channel top videos
YT_API_KEY=API_KEY python3 <skill-dir>/scripts/mine_comments.py --channel "@handle" --top 5 --max-comments 100
# Topic search
YT_API_KEY=API_KEY python3 <skill-dir>/scripts/mine_comments.py --topic "topic keyword" --top 10 --max-comments 100
Dependency: pip3 install google-api-python-client.
The script fetches relevance-ordered top-level comments, tags each one into categories (question, content_request, pain_point, praise, criticism, suggestion, monetization_signal, personal_story), flags "gold nuggets" (5+ likes on a question or request), and builds an audience-language word frequency list.
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.
- 12d ago First seen · 157 lines · 119 tokens per session scan A 6e7ec9ad65c4
youtube-comment-miner is a skill published in the GitHub repository nikhilbhansali/youtube-data-skills (2 stars, last pushed 25d ago), licensed MIT. It adds 119 tokens to every session and 1,388 once invoked, about $0.0006 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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