YouTube Mining — World Code Edition

You pull recent videos from pre-selected YouTube channels, download their transcripts, and generate content ideas the user can actually use. One pass. No back-and-forth.

Before Starting — Check Dependencies

Run this silently:

bash

which yt-dlp

If
yt-dlp
is NOT installed, stop and tell the user:

yt-dlp
is required but not installed.
Install it for your platform:
macOS:
brew install yt-dlp
Windows:
winget install yt-dlp
Linux:
pip install yt-dlp
or your package manager
Universal:
pip install yt-dlp
Then run
/boring-youtube-mining
again.

Do not proceed without

yt-dlp

. Stop gracefully.

Before Starting — Load World Code (Optional)

Try to read these files silently:

```
world-code/voice.md
```
— Voice rules (NOT applied to output — this is research, not published content)
```
world-code/conversation.md
```
— Bridge structure (walls, struggles, goblins, treasures)

If conversation.md exists: Use the Bridge to filter and prioritize ideas. Every idea gets mapped to a wall, struggle, or goblin. Ideas that don't connect to any get deprioritized (still listed, just flagged as "no Bridge connection").

If conversation.md doesn't exist: Generate ideas purely from transcript analysis. Don't nag about missing files.

Step 1: Load Channel List

Read

settings/youtube-channels.md

If the file doesn't exist, create it with starter content and tell the user:

I created
settings/youtube-channels.md
with some example channels. Edit it in Obsidian to add the channels you want to mine, then run
/boring-youtube-mining
again.

Starter content for

settings/youtube-channels.md

markdown

# YouTube Channels

Add channels you want to mine for content ideas. Use the @ handle format.
Add a short description so Claude knows the context.

- @AlexHormozi - Business, offers, scaling
- @ChrisDo - Branding, pricing, positioning

Stop after creating the file. Let the user configure it first.

Step 2: Fetch Recent Videos

For each channel in the list, run:

bash

yt-dlp --flat-playlist --playlist-items 1:5 --print "%(id)s | %(title)s | %(duration_string)s" "https://www.youtube.com/@{handle}/videos" 2>/dev/null

Process channels sequentially (not in parallel) to avoid rate limiting.

Present the results as a numbered list:

## Recent Videos

### @AlexHormozi
1. [dQw4w9WgXcQ] How to Price Your Offer (12:34)
2. [abc123def] The $100M Framework Nobody Uses (18:22)
...

### @ChrisDo
3. [xyz789ghi] Why Your Brand Is Invisible (9:45)
...

Ask the user:

Which videos should I analyze? Enter numbers (e.g., "1, 3, 5") or "all".

If a channel handle fails to resolve, report it and continue with the remaining channels:

Could not fetch videos from @BadHandle — check the handle in
settings/youtube-channels.md
.

Step 3: Download Transcripts

For each selected video, first check if a cached transcript exists:

bash

ls "content/youtube-transcripts/{video_id}.md" 2>/dev/null

If cached: Skip download, read from cache. Tell the user:

Transcript for "{title}" already cached — skipping download.

If not cached: Download the auto-generated English captions:

bash

yt-dlp --write-auto-sub --sub-lang en --sub-format vtt --skip-download -o "content/youtube-transcripts/%(id)s" "https://www.youtube.com/watch?v={video_id}" 2>/dev/null

Then clean the VTT file and save as markdown. Create the directory if needed:

bash

mkdir -p "content/youtube-transcripts"

Cleaning VTT Captions

The raw VTT file contains timestamps and duplicate lines. Clean it:

Strip all timestamp lines (lines matching
```
XX:XX:XX.XXX --> XX:XX:XX.XXX
```
)
Strip the
```
WEBVTT
```
header and
```
Kind:
```
/
```
Language:
```
metadata lines
Remove duplicate consecutive lines (VTT repeats lines across cue boundaries)
Remove position/alignment tags like
```
<c>
```
,
```
</c>
```
,
```
align:start position:0%
```
Join into paragraphs (group sentences, add line breaks at natural pauses)

Save as

content/youtube-transcripts/{video_id}.md

with frontmatter:

markdown

---
video_id: {video_id}
title: {video title}
channel: {channel handle}
date_fetched: {YYYY-MM-DD}
url: https://www.youtube.com/watch?v={video_id}
---

# {video title}

**Channel:** {channel handle}
**URL:** https://www.youtube.com/watch?v={video_id}

## Transcript

{cleaned transcript text}

Delete the raw VTT file after conversion.

Edge Cases

No English auto-captions available: Skip the video with a message:

No English captions available for "{title}" — skipping.
Very long transcripts (estimated 10,000+ words): Chunk-summarize before idea generation. Break into ~3,000 word sections, summarize each section's key points, then use the summaries for idea generation. Note in the output that the transcript was summarized.

Step 4: Generate Ideas

For each transcript, generate ideas through two lenses:

Lens 1: Direct Response

How would the user respond to this video's ideas? Generate 2-3 ideas:

Agree & Expand — They made a point you also believe. What's your unique angle on it?
Disagree & Counter — They said something you see differently. What's your take?
Build On — They touched on something but stopped short. Where would you take it?

Lens 2: Gap Ideas

What's missing? Generate 1-2 ideas:

Topics they mentioned but didn't go deep on
Adjacent topics their audience would care about but weren't covered
The question their video raises but doesn't answer

Per Idea, Include:

Field	Description
Idea title	Sharp, specific — not "Thoughts on pricing" but "Why Hourly Pricing Kills Solo Businesses"
Angle	Direct Response (agree/disagree/expand) or Gap
Source	Video title + timestamp range if identifiable
Your take (1-2 sentences)	The core argument you'd make
Bridge mapping	Which wall/struggle/goblin this connects to (if conversation.md exists)
Content type	Post, thread, email, essay, video script, carousel
Draft hook	One opening line that would stop the scroll

Quality Over Quantity

3-5 ideas per video. Not 10. Not 20. The best 3-5.
Every idea must pass the "would I actually make this?" test
If an idea is generic ("Content is important"), kill it
Ideas without a clear angle aren't ideas — they're topics. Topics aren't useful.

Bridge-First Filtering (when conversation.md exists)

After generating all ideas, sort them:

Strong Bridge connection — directly maps to a wall, struggle, or goblin
Loose Bridge connection — related to the user's world but not a direct map
No Bridge connection — interesting but disconnected from their World Code

Group 3 still gets listed but flagged. The user decides if it's worth pursuing.

Step 5: Save Output

Write the output file to

content-ideas/youtube-mining-{YYYY-MM-DD}.md

markdown

---
type: youtube-mining
date: {YYYY-MM-DD}
channels_mined: [{list of channels}]
videos_analyzed: {count}
ideas_generated: {count}
---

# YouTube Mining — {YYYY-MM-DD}

## Sources

| Video | Channel | Ideas |
|-------|---------|-------|
| {title} | {channel} | {count} |
...

## Ideas

### From: "{video title}" (@channel)

#### 1. {Idea Title}

- **Angle:** {Direct Response — Agree/Disagree/Expand | Gap}
- **Source:** {video title}, ~{timestamp context if available}
- **Your take:** {1-2 sentences}
- **Bridge:** {wall/struggle/goblin or "No direct connection"}
- **Content type:** {post/thread/email/essay/video/carousel}
- **Draft hook:** "{opening line}"

---

{repeat for each idea}

## Bridge Summary

### Strong Connections
- {idea} → {wall/struggle}
...

### No Connection
- {idea} — interesting but not tied to your current World Code
...

## Next Steps

- Pick an idea and run `/boring-copywriting` to draft it
- Run `/boring-social-content` to turn an idea into platform-specific posts
- Run `/boring-remix` to generate multiple angles on your favorite idea

Step 6: Wrap Up

After saving, tell the user:

Saved {X} ideas to
content-ideas/youtube-mining-{date}.md
.
{count} ideas with strong Bridge connections, {count} without.
Pick an idea and I can draft it with
/boring-copywriting
, turn it into social posts with
/boring-social-content
, or remix it with
/boring-remix
.

That's it. No recap of the process. No lecture on content strategy.

Key Principles

One pass, full output. Fetch → transcripts → ideas → save. No stopping to ask "should I continue?"
Research output, not published content. No voice applied. No polishing. Raw strategic ideas.
Caching is non-negotiable. Never re-download a transcript. Check the cache first, always.
Bridge-first when available. The World Code connection is what makes this useful instead of just interesting.
Sequential channel processing. Don't hammer YouTube with parallel requests.
3-5 quality ideas per video. Restraint is the skill. Anyone can generate 50 mediocre ideas.
Draft hooks matter. An idea without a hook is just a topic. Topics are cheap.
Don't explain the process. The user doesn't need a play-by-play of "now I'm downloading transcripts." Just do it and show the results.

Related Skills

boring-copywriting — Draft full content from a mined idea
boring-social-content — Turn ideas into platform-specific posts
boring-remix — Generate multiple angles on a single idea
boring-content-strategy — Broader content planning using mined insights

boring-youtube-mining

NPX Install

Tags

SKILL.md Content

YouTube Mining — World Code Edition

Before Starting — Check Dependencies

Before Starting — Load World Code (Optional)

Step 1: Load Channel List

Step 2: Fetch Recent Videos

Step 3: Download Transcripts

Cleaning VTT Captions

Edge Cases

Step 4: Generate Ideas

Lens 1: Direct Response

Lens 2: Gap Ideas

Per Idea, Include:

Quality Over Quantity

Bridge-First Filtering (when conversation.md exists)

Step 5: Save Output

Step 6: Wrap Up

Key Principles

Related Skills