Leaderboard/Automation/youtube-fetcher-to-markdown
Last commit on September 5, 2026·Created on March 4, 2026

JimmySadek/youtube-fetcher-to-markdown

Converts YouTube transcripts and metadata into structured Markdown for knowledge bases.
Combined rank
#517
across all skills
In Automation
#39
category rank
Stars
480
+1.9% in last 7d
Forks
36
0.0% in last 7d
Watchers
2
0.0% in last 7d
Traction scoreGitHub stars can be faked, so popularity alone can be misleading. Traction Score looks for broader signs of recent attention, adoption, and active maintenance.
TL;DR

This skill retrieves captions and subtitles from YouTube videos without requiring an API key. It allows users to archive spoken content as Obsidian-ready notes or analyze transcripts to answer specific questions with timestamped references.

By integrating creator metadata, chapters, and source provenance, it helps researchers and automation builders transform video content into searchable, text-based documentation.

WHO IT'S FOR
Obsidian users
archiving YouTube content as markdown notes
AI agent / automation builders
integrating YouTube transcript retrieval into workflows
Researchers and students
summarizing or analyzing spoken video content
Content archivists
exporting subtitles in multiple standard formats
Repository contents

1 skill file

Compatible AgentsThe repository documents support for these agents. The skills may also work with other agents that can load SKILL.md files, but they may need some setup or small changes.

Use this skill

Follow the documented setup, then try a first task.

Skills CLI with macOS/Linux runtime setup

Installs: Installs the youtube-fetcher-to-markdown skill from JimmySadek/youtube-fetcher-to-markdown.

Before you start
  • An environment with the documented `npx` command available
  • Python 3.8–3.14

Platform: macOS/Linux

Run from: Installed skill directory

  1. Run this terminal command to install the skill.

    npx skills add JimmySadek/youtube-fetcher-to-markdown
  2. In a terminal, change to the installed skill directory, then create an isolated environment, install the required dependencies, and check them with these commands.

    python3 -m venv .venv
    .venv/bin/python -m pip install -r requirements.txt
    .venv/bin/python scripts/fetch_transcript.py --check-deps
  3. Before using the documented `python3` examples, activate the environment with `source .venv/bin/activate`; alternatively, use the virtual environment's full interpreter path every time. An agent must also use that interpreter. If the skill installation is read-only, create the environment in a writable location and pass the full path to `requirements.txt`.

README.md · Checked Sep 18, 2026

Give it something to do.

Suggested first task

Summarize a captioned YouTube video

Uses youtube-fetcher

  • A public YouTube URL or video ID
  • Accessible captions for the video
  • A Python interpreter with the skill's dependencies installed
  • Network access to YouTube captions
Use the youtube-fetcher skill to summarize what was said in [YOUTUBE URL]. Include timestamp links for the most important moments where useful. Retrieve the captions for analysis without saving an extra archival note unless needed. Replace [YOUTUBE URL] with a public YouTube URL whose captions are accessible.
SKILL.md · Checked Sep 18, 2026README.md · Checked Sep 18, 2026