Registry indexed
>-
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 2.0
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.
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.
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?
name: yt-viral description: >- 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.
---
name: yt-viral
description: >-
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.
---
# 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.
```bash
python3 swipe.py collected.json --min 2.0
```
## Collecting 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.
```json
[{"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](../yt-script/hooks.json) - 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?**
Free to get does not mean free to run. Price labels are not safety ratings. Submit pricing information →
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
License: MIT
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
Version reported in registry metadata; check source releases before relying on it.
Quality
60/100
Promising
Trust
50/100
Do not auto-install
Audit
70/100
Needs review
Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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"documentation": "Thin public metadata",
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"GitHub adoption: 23 GitHub stars",
"Stars/forks activity: 23 stars, 4 forks; issue activity unavailable in current metadata",
"README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context",
"Dependency/runtime risk: command execution surface, credential or environment access"
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"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"GitHub adoption: 23 GitHub stars"
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"Safety: 30/100 Avoid automatic install",
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}Listing source
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