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: []
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.
Use terminal with the Python from a PM-prepared Hermes source checkout. The youtube extra declares the helper's dependency; do not install packages into Hermes with raw pip or project-discovering uv run.
From that checkout, first follow the isolated development-home setup in Package Management, then prepare the extra and reactivate before running the helper:
source ./activate python -c "import pm; pm.sync_venv(['youtube'], explicit=True)" source ./activate python -c "import youtube_transcript_api; print(youtube_transcript_api.__file__)"
On Windows, use . .\activate.ps1 instead of source ./activate. If the terminal runs on a different host or in a sandbox, use an explicitly isolated helper environment there, not the agent's production environment. Run every command below with the interpreter whose import check succeeded.
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 python SKILL_DIR/scripts/fetch_transcript.py "https://youtube.com/watch?v=VIDEO_ID" # Plain text (good for piping into further processing) python SKILL_DIR/scripts/fetch_transcript.py "URL" --text-only # With timestamps python SKILL_DIR/scripts/fetch_transcript.py "URL" --timestamps # Specific language with fallback chain python SKILL_DIR/scripts/fetch_transcript.py "URL" --language tr,en
After fetching the transcript, format it based on what the user asks for:
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
terminal and the prepared Python with --text-only --timestamps.--language to get any available transcript. If still empty, tell the user the video likely has transcripts disabled.--language to fetch any available transcript, then note the actual language to the user.