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youtube-content — Claude Code skill for YouTube transcripts

Fetch a YouTube transcript and turn it into chapters, a summary, a thread, or a blog post. Useful when you need to reshape video content as text.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add NousResearch/hermes-agent --skill youtube-content -a claude-code
Open on GitHub

What youtube-content does

The skill retrieves a transcript from a YouTube URL or video ID, then formats it as timestamped chapters, a summary, a Twitter/X thread, a blog post, or quotes. You can request timestamps and select a language with fallbacks. If you don’t choose a format, it produces a summary.

It includes the Python script scripts/fetch_transcript.py, which accepts standard YouTube links, short links, Shorts, embeds, and live links. Before running it, prepare an isolated Hermes Agent environment, add the youtube extra, and use the Python interpreter that successfully imports youtube_transcript_api. Without that setup, transcript fetching won’t run. If the result is empty, the skill retries without a language selection; if that also fails, it tells you transcripts are likely disabled.

What it helps with

  • fetch a transcript from a YouTube link
  • split a video into timestamped chapters
  • condense a video into a short summary
  • reshape video content as a Twitter/X thread
  • draft a blog post or collect timestamped quotes

Example prompts for the agent

  • Summarize this video: https://youtube.com/watch?v=VIDEO_ID.
  • Get the transcript with timestamps and organize it into chapters: URL.
  • Turn this video's transcript into a blog post with headings and key takeaways: URL.

How to install youtube-content

1Skills CLI (Vercel)

npx skills add NousResearch/hermes-agent --skill youtube-content -a claude-code

2Manually: put the files in place

~/.claude/skills/youtube-content/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/youtube-content/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about youtube-content

How do I install youtube-content in Claude Code?

Run npx skills add NousResearch/hermes-agent --skill youtube-content -a claude-code. The skill file will be at ~/.claude/skills/youtube-content/SKILL.md.

What does youtube-content do?

It retrieves YouTube transcripts and formats them as summaries, chapters, threads, blog posts, or timestamped quotes.

What does youtube-content need to run?

Prepare an isolated Hermes Agent environment with the youtube extra. Run the script with a Python interpreter that imports youtube_transcript_api.

Source text

SKILL.md · MIT
---
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 `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](https://hermes-agent.nousresearch.com/docs/reference/package-management#developer-workflow),
then prepare the extra and reactivate before running the helper:

```bash
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.

## 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
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
```

## 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 `terminal` and the prepared Python 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**: repeat PM preparation and reactivation above, then verify the helper uses that Python. Do not repair the selected generation with pip.

© Teknium (teknium1), Hermes Agent · MIT · NousResearch/hermes-agent

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