youtube-content

name	youtube-content
description	YouTube transcripts to summaries, threads, blogs.
platforms	["linux","macos","windows"]

YouTube Content Tool

When to use

Reach for this when the user shares a YouTube URL or video link, asks to summarize a video, requests a transcript, or wants to pull and reshape content from any YouTube video. It converts transcripts into structured formats (chapters, summaries, threads, blog posts).

Extract transcripts from YouTube videos and transform them into useful formats.

Setup

Use uv so the dependency is installed into the same Ion-managed environment that runs the helper script:

uv 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.

# JSON output with metadata
uv run python3 SKILL_DIR/scripts/fetch_transcript.py "https://youtube.com/watch?v=VIDEO_ID"

# Plain text (good for piping into further processing)
uv run python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --text-only

# With timestamps
uv run python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --timestamps

# Specific language with fallback chain
uv run python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --language tr,en

Output Formats

Once the transcript is fetched, shape it according to what the user requests:

• 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 via uv run python3.
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 uv pip install youtube-transcript-api and retry.