yt-viral
Skill47 starsChanged 2 months agoMITView on GitHub
Find what is actually working in the user's niche on YouTube and rank it by how far each video beat its own channel, then name the formula. Use for "what's working right now", "find viral videos in my niche", "why did this blow up", competitor research, or a swipe file.
6 other projects use a version of this, 4 of them edited.
Adopted by
Most recently taken up by
- gladosAagman/youtube-agent-skillword for word, first seen Nov 15, 2026
- utillayer/youtube-agent-skilledited, first seen Nov 8, 2026
- uplika/uplika-pluginedited, first seen Oct 25, 2026
- swayamdhawan/youtube-agentword for word, first seen Oct 15, 2026
- ahmedsakri/youtube-agent-proedited, first seen Oct 15, 2026
- nessalazne/youtube-agent-skilledited, first seen Sep 23, 2026
Other versions6 projects use a version of this.
Word for word · 2
- gladosAagman/youtube-agent-skill★ 1100% same
- swayamdhawan/youtube-agent★ 0100% same
Edited · 4
- utillayer/youtube-agent-skill★ 1014% same
- nessalazne/youtube-agent-skill★ 568% same
- uplika/uplika-plugin★ 325% same
- ahmedsakri/youtube-agent-pro★ 157% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository10 other files it gives its agents.
- yt-auditSkill
- yt-chaptersSkill
- yt-commentSkill
- yt-editSkill
- yt-packageSkill
- yt-planSkill
- yt-retentionSkill
- yt-scriptSkill
- yt-seoSkill
- yt-shortsSkill
The file
Files
yt-viral
Raw view counts rank channel size, not ideas. This ranks by multiple over each channel's own median, which is the only version of the question that is about the video.
python3 swipe.py collected.json --min 2.0Collecting the input
You need at least four videos per channel or a median means nothing, and the tool will skip the
channel and tell you it did. Collect them however the user prefers - yt-dlp --flat-playlist -J
against a channel URL is the fastest, the public page works, a manual list works.
[{"channel":"...","title":"...","views":412000,"url":"...","duration":613}]Read, do not scrape. Public listings only, never a logged-in session, never the user's own account credentials.
Reading the output
The multiple is the signal. The formula line is a judgement about the TITLE, matched against the 21 formulas - it is not a claim about why the video worked, and you should say so when you present it.
What to hand back: the top five with their multiples, the formula each used, and the ONE structural thing they share. Then the harder line - which of those the user could actually make this week, in their voice, with what they have.
The gate
Nothing here publishes. This skill writes and you publish. Every output ends in a block the user copies, and the last line of every run is the question: ship it, or change it?
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.