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---
name: youtube-content
description: "YouTube transcripts to summaries, threads, blogs."
platforms: [linux, macos, windows]
---
# YouTube Content Tool
## When to use
Use when the user shares a YouTube URL or video link, asks to summarize a video, requests a transcript, or wants to extract and reformat content from any YouTube video. Transforms transcripts into structured content (chapters, summaries, threads, blog posts).
Extract transcripts from YouTube videos and convert them into useful formats.
## Setup
```bash
pip install youtube-transcript-api
```
## Helper Script
`SKILL_DIR` is the directory containing this SKILL.md file. The script accepts any standard YouTube URL format, short links (youtu.be), shorts, embeds, live links, or a raw 11-character video ID.
```bash
# JSON output with metadata
python3 SKILL_DIR/scripts/fetch_transcript.py "https://youtube.com/watch?v=VIDEO_ID"
# Plain text (good for piping into further processing)
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --text-only
# With timestamps
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --timestamps
# Specific language with fallback chain
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --language tr,en
```
## Output Formats
After fetching the transcript, format it based on what the user asks for:
- **Chapters**: Group by topic shifts, output timestamped chapter list
- **Summary**: Concise 5-10 sentence overview of the entire video
- **Chapter summaries**: Chapters with a short paragraph summary for each
- **Thread**: Twitter/X thread format — numbered posts, each under 280 chars
- **Blog post**: Full article with title, sections, and key takeaways
- **Quotes**: Notable quotes with timestamps
### Example — Chapters Output
```
00:00 Introduction — host opens with the problem statement
03:45 Background — prior work and why existing solutions fall short
12:20 Core method — walkthrough of the proposed approach
24:10 Results — benchmark comparisons and key takeaways
31:55 Q&A — audience questions on scalability and next steps
```
## Workflow
1. **Fetch** the transcript using the helper script with `--text-only --timestamps`.
2. **Validate**: confirm the output is non-empty and in the expected language. If empty, retry without `--language` to get any available transcript. If still empty, tell the user the video likely has transcripts disabled.
3. **Chunk if needed**: if the transcript exceeds ~50K characters, split into overlapping chunks (~40K with 2K overlap) and summarize each chunk before merging.
4. **Transform** into the requested output format. If the user did not specify a format, default to a summary.
5. **Verify**: re-read the transformed output to check for coherence, correct timestamps, and completeness before presenting.
## Error Handling
- **Transcript disabled**: tell the user; suggest they check if subtitles are available on the video page.
- **Private/unavailable video**: relay the error and ask the user to verify the URL.
- **No matching language**: retry without `--language` to fetch any available transcript, then note the actual language to the user.
- **Dependency missing**: run `pip install youtube-transcript-api` and retry.

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# Output Format Examples
## Chapters
```
00:00 Introduction
02:15 Background and motivation
05:30 Main approach
12:45 Results and evaluation
18:20 Limitations and future work
21:00 Q&A
```
## Summary
A 5-10 sentence overview covering the video's main points, key arguments, and conclusions. Written in third person, present tense.
## Chapter Summaries
```
## 00:00 Introduction (2 min)
The speaker introduces the topic of X and explains why it matters for Y.
## 02:15 Background (3 min)
A review of prior work in the field, covering approaches A, B, and C.
```
## Thread (Twitter/X)
```
1/ Just watched an incredible talk on [topic]. Here are the key takeaways: 🧵
2/ First insight: [point]. This matters because [reason].
3/ The surprising part: [unexpected finding]. Most people assume [common belief], but the data shows otherwise.
4/ Practical takeaway: [actionable advice].
5/ Full video: [URL]
```
## Blog Post
Full article with:
- Title
- Introduction paragraph
- H2 sections for each major topic
- Key quotes (with timestamps)
- Conclusion / takeaways
## Quotes
```
"The most important thing is not the model size, but the data quality." — 05:32
"We found that scaling past 70B parameters gave diminishing returns." — 12:18
```

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#!/usr/bin/env python3
"""
Fetch a YouTube video transcript and output it as structured JSON.
Usage:
python fetch_transcript.py <url_or_video_id> [--language en,tr] [--timestamps]
Output (JSON):
{
"video_id": "...",
"language": "en",
"segments": [{"text": "...", "start": 0.0, "duration": 2.5}, ...],
"full_text": "complete transcript as plain text",
"timestamped_text": "00:00 first line\n00:05 second line\n..."
}
Install dependency: pip install youtube-transcript-api
"""
import argparse
import json
import re
import sys
def extract_video_id(url_or_id: str) -> str:
"""Extract the 11-character video ID from various YouTube URL formats."""
url_or_id = url_or_id.strip()
patterns = [
r'(?:v=|youtu\.be/|shorts/|embed/|live/)([a-zA-Z0-9_-]{11})',
r'^([a-zA-Z0-9_-]{11})$',
]
for pattern in patterns:
match = re.search(pattern, url_or_id)
if match:
return match.group(1)
return url_or_id
def format_timestamp(seconds: float) -> str:
"""Convert seconds to HH:MM:SS or MM:SS format."""
total = int(seconds)
h, remainder = divmod(total, 3600)
m, s = divmod(remainder, 60)
if h > 0:
return f"{h}:{m:02d}:{s:02d}"
return f"{m}:{s:02d}"
def fetch_transcript(video_id: str, languages: list = None):
"""Fetch transcript segments from YouTube.
Returns a list of dicts with 'text', 'start', and 'duration' keys.
Compatible with youtube-transcript-api v1.x.
"""
try:
from youtube_transcript_api import YouTubeTranscriptApi
except ImportError:
print("Error: youtube-transcript-api not installed. Run: pip install youtube-transcript-api",
file=sys.stderr)
sys.exit(1)
api = YouTubeTranscriptApi()
if languages:
result = api.fetch(video_id, languages=languages)
else:
result = api.fetch(video_id)
# v1.x returns FetchedTranscriptSnippet objects; normalize to dicts
return [
{"text": seg.text, "start": seg.start, "duration": seg.duration}
for seg in result
]
def main():
parser = argparse.ArgumentParser(description="Fetch YouTube transcript as JSON")
parser.add_argument("url", help="YouTube URL or video ID")
parser.add_argument("--language", "-l", default=None,
help="Comma-separated language codes (e.g. en,tr). Default: auto")
parser.add_argument("--timestamps", "-t", action="store_true",
help="Include timestamped text in output")
parser.add_argument("--text-only", action="store_true",
help="Output plain text instead of JSON")
args = parser.parse_args()
video_id = extract_video_id(args.url)
languages = [l.strip() for l in args.language.split(",")] if args.language else None
try:
segments = fetch_transcript(video_id, languages)
except Exception as e:
error_msg = str(e)
if "disabled" in error_msg.lower():
print(json.dumps({"error": "Transcripts are disabled for this video."}))
elif "no transcript" in error_msg.lower():
print(json.dumps({"error": f"No transcript found. Try specifying a language with --language."}))
else:
print(json.dumps({"error": error_msg}))
sys.exit(1)
full_text = " ".join(seg["text"] for seg in segments)
timestamped = "\n".join(
f"{format_timestamp(seg['start'])} {seg['text']}" for seg in segments
)
if args.text_only:
print(timestamped if args.timestamps else full_text)
return
result = {
"video_id": video_id,
"segment_count": len(segments),
"duration": format_timestamp(segments[-1]["start"] + segments[-1]["duration"]) if segments else "0:00",
"full_text": full_text,
}
if args.timestamps:
result["timestamped_text"] = timestamped
print(json.dumps(result, ensure_ascii=False, indent=2))
if __name__ == "__main__":
main()