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For 14 of 74 compressed skills, the original description contained trigger keywords, technique counts, attribution, or use-case phrases not covered by the existing body content. Prepends a 'When to use' / 'What's inside' block near the top so the agent still has the full context when the skill is loaded. Skills salvaged: - codex, ascii-video, creative-ideation, excalidraw, manim-video, p5js - gif-search, heartmula, youtube-content - lm-evaluation-harness, obliteratus, vllm, axolotl - powerpoint Remaining 60 skills were verified to already cover the dropped content in their existing body sections (When to Use, overview, intro prose) or had short descriptions fully captured by the new compressed form.
3.1 KiB
3.1 KiB
name, description
| name | description |
|---|---|
| youtube-content | YouTube transcripts to summaries, threads, blogs. |
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
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
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
- Fetch the transcript using the helper script with
--text-only --timestamps. - Validate: confirm the output is non-empty and in the expected language. If empty, retry without
--languageto get any available transcript. If still empty, tell the user the video likely has transcripts disabled. - Chunk if needed: if the transcript exceeds ~50K characters, split into overlapping chunks (~40K with 2K overlap) and summarize each chunk before merging.
- Transform into the requested output format. If the user did not specify a format, default to a summary.
- 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
--languageto fetch any available transcript, then note the actual language to the user. - Dependency missing: run
pip install youtube-transcript-apiand retry.