video-toolkit

A tool for analyzing and editing video with FFmpeg and Whisper. FFmpeg processes video files, while Whisper converts spoken audio into text.

In plain words
What is it for?
Use it to inspect or summarize videos, transcribe their speech, and clip, merge, or split files.
Why use it?
It provides a way to work with video files that cannot be read like ordinary text files.

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/emdashcodes/claude-code-plugins/video-toolkit
Any agent
npx skills add emdashcodes/claude-code-plugins --skill video-toolkit
Clone the repo
git clone --depth 1 https://github.com/emdashcodes/claude-code-plugins

Made for: Claude Code, Codex.

Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 14,543 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. 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 $0.00074 $0.14543
Opus 5 $0.00037 $0.07272
Sonnet 5 $0.00015 $0.02909
Haiku 4.5 $0.00007 $0.01454

Measured 2d ago against content hash 56021b278fee, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

video-toolkit scanned grade C with 1 finding 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.

The scan reads SKILL.md. This mod also ships 9 executable files (scripts/analyze_audio_gemini.py, scripts/analyze_video.sh, scripts/edit_video.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

4. Clean up: `rm -rf /tmp/video-toolkit-[timestamp]/partial-analyses`
plugins/video-toolkit/skills/video-toolkit/SKILL.md · 1,780 lines

How it starts

The opening of the file, as written. The whole thing — 1,780 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Video Toolkit

Comprehensive video processing skill combining editing capabilities with multi-modal analysis (visual frames + audio transcription).

When to Use This Skill

Activate this skill when:

  • User shares a video file (.mov, .mp4, .avi, .mkv, .webm, etc.)
  • User asks to analyze, summarize, or understand video content
  • User requests video editing operations (clip, merge, split)
  • User asks questions about what's in a video
  • You encounter "cannot read binary files" errors when trying to read video files
  • Guides agents to use proper video analysis workflow

What this means for users:

When you share a video file, Claude will automatically recognize it and offer to analyze it properly using the video-toolkit, rather than attempting to read the binary file directly.

Prerequisites

Required Dependencies:

  1. FFmpeg - Video processing and frame extraction

    • Installation handled by scripts/install_dependencies.sh
    • Verify: ffmpeg -version
  2. Python 3.8+ with virtual environment

    • Installation handled by scripts/install_dependencies.sh
  3. OpenAI Whisper - Speech transcription (local, no API key required)

    • Installed via pip in .venv
    • Model: base (good balance of speed/accuracy)
    • Other models available: tiny.en, small, medium, large
  4. Google Gemini API - Audio analysis and music detection

    • Installed via pip in .venv
    • Requires API key (see setup below)
    • Model: gemini-2.5-flash
  5. Shazam API - Music identification

    • Installed via pip in .venv (shazamio)
    • No API key required (uses public endpoint)

Setup:

Step 1: Install Dependencies

Run the installation script on first use:

bash ${CLAUDE_PLUGIN_ROOT}/skills/video-toolkit/scripts/install_dependencies.sh

This creates a Python virtual environment at ${CLAUDE_PLUGIN_ROOT}/skills/video-toolkit/.venv/ and installs the required packages (ffmpeg-python, openai-whisper, google-genai, shazamio).

Step 2: Configure API Keys

Read the full file on GitHub · 1,780 lines

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 · 1,780 lines · 74 tokens per session scan C 56021b278fee

Subscribe to this mod's changes

video-toolkit is a skill published in the GitHub repository emdashcodes/claude-code-plugins (13 stars, last pushed 1mo ago), licensed MIT. It adds 74 tokens to every session and 14,543 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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