video_toolkit

video_toolkit is a skill for Claude Code, Codex from digitalsamba/claude-code-video-toolkit. It costs 60 tokens per session (5,425 once invoked), scanned A, original, MIT.

A toolkit guide for making short explainer videos from a brief, including submitting a scene description, checking the job, and retrieving a quality-checked MP4.

In plain words
What is it for?
Use it to create explainer videos or assemble custom video work with the toolkit's media-generation tools.
Why use it?
It describes a repeatable way to turn a written brief into a finished video and also documents separate tools for voice, images, clips, music and talking heads.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: reads .claude/ paths; mentions CLAUDE.md; positional $N argument.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is uv run tools/verify_setup.py --json # prerequisites, keys and endpoints; [x] means ready.

Good fit Use it to create explainer videos or assemble custom video work with the toolkit's media-generation tools.

Compare 6 skills from other repositories ↓
About the project

Claude Code Video Toolkit is a workspace that lets Claude Code create videos by producing scripts, voiceovers, music, visuals, and rendered MP4 files. It is for developers using AI-assisted, programmatic video production with tools such as Remotion and open-source media models. The catalogue entries provide commands, skills, instructions, and settings for this workflow.

digitalsamba/claude-code-video-toolkit · 2,453 stars · on GitHub

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/digitalsamba/claude-code-video-toolkit
agentmods
npx agentmods add skills/digitalsamba/claude-code-video-toolkit/video-toolkit

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for video_toolkit

README.md
[![agentmods](https://agentmods.dev/badge/skills/digitalsamba/claude-code-video-toolkit/video-toolkit/github.svg)](https://agentmods.dev/skills/digitalsamba/claude-code-video-toolkit/video-toolkit)
Your own site
<a href="https://agentmods.dev/skills/digitalsamba/claude-code-video-toolkit/video-toolkit"><img src="https://agentmods.dev/badge/skills/digitalsamba/claude-code-video-toolkit/video-toolkit/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for video_toolkit

Your own site · 80×15
<a href="https://agentmods.dev/skills/digitalsamba/claude-code-video-toolkit/video-toolkit"><img src="https://agentmods.dev/badge/skills/digitalsamba/claude-code-video-toolkit/video-toolkit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,425 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00060 $0.05425
Opus 5.5 $0.00024 $0.02170
Sonnet 5.5 $0.00012 $0.01085
Haiku 4.5 $0.00006 $0.00543

Measured today against content hash 6a40c7b2cd8d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

video_toolkit scanned grade A 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 today.

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.

Makes network callslowCapability

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

`{"brief","format","duration_s",...}` on stdin and prints a spec JSON (`claude -p`, a curl to any model, your own
skills/video-toolkit/SKILL.md · 336 lines

How it starts

The opening of the file, as written. The whole thing — 336 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Video Toolkit

Turn a brief into a finished MP4 with claude-code-video-toolkit. This skill is written for any agent runtime: Claude Code, OpenClaw, Codex, Hermes, a bare API loop with a run_tool call, or an MCP client. Nothing here depends on how your runtime backgrounds work, because the long work runs in a detached job you poll.

Where the toolkit is

Every command below runs from the toolkit root. Find it, in this order:

  1. $VIDEO_TOOLKIT_ROOT if set (also honoured by the toolkit's own scripts);
  2. $VIDEO_TOOLKIT_DIR (the name longarm uses);
  3. a claude-code-video-toolkit/ directory under your workspace or home.
cd "${VIDEO_TOOLKIT_ROOT:-${VIDEO_TOOLKIT_DIR:-$HOME/claude-code-video-toolkit}}"
uv run tools/verify_setup.py --json     # prerequisites, keys and endpoints; [x] means ready

Never run a tool from inside a project directory: tools resolve paths relative to the toolkit root. If your runtime can't cd, pass --directory: uv run --directory /path/to/toolkit tools/video_job.py ....

No shell at all? Use the MCP server instead: uv run --directory /path/to/toolkit --extra mcp tools/video_mcp.py exposes video_estimate, video_submit, video_status, video_result and video_list_presets over stdio. Same flow as below, same JSON.

The quick path: estimate → submit → poll → result

tools/video_job.py is one async entrypoint. submit returns in seconds with a job id; a detached worker runs the whole pipeline (voiceover → visuals → captions → build → QC); every later call is short and reads state from disk. That is how it fits a per-call time limit, and it survives you going away between turns.

1. Write the spec (you are the LLM)

A spec is a list of scenes, each with narration text and one visual. Budget about 2.4 words a second of narration; a 45 s video is ~100 words in 3 to 5 scenes.

{
  "title": "Why do we have leap years?",
  "format": "9:16",
  "voice": {"provider": "qwen3", "speaker": "Ryan", "tone": "warm", "maxWpm": 165},
  "scenes": [
    {"slug": "hook",
     "text": "Every four years, February gets an extra day. Why? Because a year isn't 365 days long.",
     "visual": {"kind": "ltx", "prompt": "Slow orbital shot of Earth turning in space, sunlight sweeping the oceans, cinematic, no text"}},
    {"slug": "quarter",
     "text": "Earth takes about 365 and a quarter days to orbit the sun. Ignore the quarter and the calendar drifts.",
     "visual": {"kind": "ideogram", "caption": { "...filled from the caption template below..." }}},
    {"slug": "cta",
     "text": "So every fourth year we add one day back. Follow for one concept a week.",
     "visual": {"kind": "ideogram", "caption": { "...filled from the caption template below..." }}}
  ]
}

Read the full file on GitHub · 336 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. today Changed · +1 lines 6a40c7b2cd8d
  2. 4d ago Changed · +13 lines 109c9c391b56
  3. 5d ago First seen · 322 lines · 60 tokens per session scan A 9958f6a88a6a

Subscribe to this mod's changes

video_toolkit is a skill published in the GitHub repository digitalsamba/claude-code-video-toolkit (2,453 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 5,425 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-11-01.

Related

video_toolkit compared with skills from other repositories

video_toolkit next to 6 skills from other repositories
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