youtube-transcript

A tool for getting the written transcript of a YouTube video and extracting video frames at points where the speaker refers to something visible. A transcript is the spoken content in text form.

In plain words
What is it for?
Use it to analyse YouTube tutorials, conference talks, and other videos with subtitles or automatic captions. It can provide the transcript and visual references for further review.
Why use it?
It helps when the meaning depends on both what a speaker says and what appears on screen. The timestamps and images make tutorials, talks, and demonstrations easier to inspect.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/b33eep/claude-code-setup/youtube-transcript
Any agent
npx skills add b33eep/claude-code-setup --skill youtube-transcript
Clone the repo
git clone --depth 1 https://github.com/b33eep/claude-code-setup

Made for: Claude Code, Codex.

Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,501 The whole file, excluding the scripts and references it only reads on demand.
Security scan D 3 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00030 $0.01501
Opus 5 $0.00015 $0.00750
Sonnet 5 $0.00006 $0.00300
Haiku 4.5 $0.00003 $0.00150

Measured 2d ago against content hash 07a5b0b3c367, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade D, and why

youtube-transcript scanned grade D with 3 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

sudo apt install ffmpeg

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

- Install deno if needed: `brew install deno` or `curl -fsSL https://deno.land/install.sh | sh`

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Install deno if needed: `brew install deno` or `curl -fsSL https://deno.land/install.sh | sh`
skills/youtube-transcript/SKILL.md · 199 lines

How it starts

The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.

YouTube Transcript Skill

Download and analyze YouTube video transcripts with automatic frame extraction at visual reference points.

Usage

/youtube-transcript <youtube-url>

What This Skill Does

  1. Downloads transcript with timestamps (YouTube auto-captions or manual subtitles)
  2. Detects visual references in the text ("look at this diagram", "as you can see here")
  3. Extracts frames at those timestamps for context
  4. Presents transcript with embedded images for analysis

Requirements

macOS

brew install yt-dlp ffmpeg

Linux (Ubuntu/Debian)

sudo apt install ffmpeg
pip install yt-dlp

Linux (Arch)

sudo pacman -S yt-dlp ffmpeg

Instructions for Claude

When the user invokes /youtube-transcript <url>:

Step 1: Check Dependencies

command -v yt-dlp >/dev/null 2>&1 || echo "MISSING: yt-dlp"
command -v ffmpeg >/dev/null 2>&1 || echo "MISSING: ffmpeg"

If missing, show installation instructions for the user's platform.

Step 2: Create Output Directory

Use the scratchpad directory for output:

# Extract video ID from YouTube URL (POSIX-compatible, works on macOS and Linux)
# Handles: youtube.com/watch?v=ID, youtu.be/ID, youtube.com/embed/ID
URL="<url>"
VIDEO_ID=$(echo "$URL" | sed -E 's/.*[?&]v=([^&]+).*/\1/;s|.*/embed/([^?/]+).*|\1|;s|.*youtu\.be/([^?/]+).*|\1|')
OUTPUT_DIR="<scratchpad>/youtube-${VIDEO_ID}"
mkdir -p "${OUTPUT_DIR}/frames"

Step 3: Download Transcript

cd "${OUTPUT_DIR}"

# Try auto-generated subtitles first, fall back to manual
yt-dlp --write-auto-sub --sub-lang en,de --skip-download --convert-subs srt -o "transcript" "<url>" 2>/dev/null || \
yt-dlp --write-sub --sub-lang en,de --skip-download --convert-subs srt -o "transcript" "<url>"

Step 4: Analyze for Visual References

Read the transcript and identify timestamps where visual content is referenced. Look for patterns:

German:

  • "schau(t)? (mal )?(hier|das)"
  • "(dieses|das|dieser) (Diagramm|Bild|Schema|Chart|Graph|Screen|Slide)"
  • "wie (du|ihr|Sie) (hier )?(siehst|sehen)"
  • "auf (dem|diesem) (Bildschirm|Screen|Slide)"
  • "hier sehen wir"

Read the full file on GitHub · 199 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 199 lines · 30 tokens per session scan D 07a5b0b3c367

Subscribe to this mod's changes

youtube-transcript is a skill published in the GitHub repository b33eep/claude-code-setup (56 stars, last pushed 3mo ago), licensed MIT. It adds 30 tokens to every session and 1,501 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it D with 3 findings (asks for root, downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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