youtube-content

name youtube-content description YouTube transcripts to summaries, threads, blogs. version 1.0.0 author Teknium (teknium1), Hermes Agent license MIT platforms ["linux","macos","windows"] metadata {"hermes":{"tags":["YouTube","Video","Transcripts","Media"],"related_skills":[]}} 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 Use uv so the dependency is installed into the same Hermes-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 python SKILL_DIR/scripts/fetch_transcript.py "https://youtube.com/watch?v=VIDEO_ID" # Plain text (good for piping into further processing) uv run python SKILL_DIR/scripts/fetch_transcript.py "URL" --text-only # With timestamps uv run python SKILL_DIR/scripts/fetch_transcript.py "URL" --timestamps # Specific language with fallback chain uv run python 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 via uv run python . 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. 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 --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.