youtube-content
The youtube-content skill extracts transcripts from YouTube videos using the youtube-transcript-api library and transforms them into multiple formats including summaries, timestamped chapters, blog posts, Twitter threads, and quoted excerpts. Use this skill when you need to analyze, repurpose, or extract information from YouTube video content without watching the full video.
git clone --depth 1 https://github.com/moltis-org/moltis /tmp/youtube-content && cp -r /tmp/youtube-content/crates/skills/src/assets/media/youtube-content ~/.claude/skills/youtube-contentSKILL.md
# YouTube Content Tool 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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