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.
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.
git clone --depth 1 https://github.com/digitalsamba/claude-code-video-toolkitnpx agentmods add commands/digitalsamba/claude-code-video-toolkit/thumbnailWrote 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.
[](https://agentmods.dev/commands/digitalsamba/claude-code-video-toolkit/thumbnail)<a href="https://agentmods.dev/commands/digitalsamba/claude-code-video-toolkit/thumbnail"><img src="https://agentmods.dev/badge/commands/digitalsamba/claude-code-video-toolkit/thumbnail/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.
<a href="https://agentmods.dev/commands/digitalsamba/claude-code-video-toolkit/thumbnail"><img src="https://agentmods.dev/badge/commands/digitalsamba/claude-code-video-toolkit/thumbnail.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00013 | $0.01891 |
| Opus 5.5 | $0.00005 | $0.00756 |
| Sonnet 5.5 | $0.00003 | $0.00378 |
| Haiku 4.5 | $0.00001 | $0.00189 |
Grade A, and why
thumbnail scanned grade A with 0 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 4d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Thumbnail
Generate a 1280×720 thumbnail for a project: a short hook phrase in big legible text, in
the brand's colours, ready for /publish --thumbnail. Wraps tools/ideogram4.py.
project.json + script + brand.json → hook phrase → JSON caption → Ideogram 4 → check text → out/thumbnail.png
Claude does the creative part: it picks the phrase and writes the caption. Ideogram renders
text reliably only from a structured JSON caption. A plain --prompt adds garbled
filler text. Load the ideogram4 skill (SKILL.md, prompting.md, examples.md §2)
before writing the caption.
Needs
IDEOGRAM_API_KEYin.env(key from developer.ideogram.ai). If it's missing, say so and stop. Cost: ~$0.10 per image at--speed QUALITY. Tell the user the total before generating more than one.
Entry Point
Step 1: Locate the project
If the user named a project, use it. Otherwise list candidates and ask:
cd /path/to/claude-code-video-toolkit && ls projects/*/project.json
If out/thumbnail.* already exists, show it and ask whether to replace it or keep it.
Step 2: Gather what the video is about
project.json is often sparse (null titles and narration), so read the content from wherever it is:
project.json:publish.title,title,name,description,brand, and each scene'stitleandnarrationVOICEOVER-SCRIPT.md, which usually has the clearest statement of the topic- The template config (
src/config/*.ts, e.g.sprint-config.tsordemo-config.ts), for the title slide text and any stats scenes.jsonfor concept-explainer-short projects
Then read brands/<brand>/brand.json. Pick 3–4 colours: a dark or light background,
the primary or accent colour, and a high-contrast text colour (usually white). Don't pass
--brand to the tool. It injects every colour in brand.json, including dividers, shadows
and greys, which muddies the palette.
Step 3: Choose the hook phrase
The thumbnail text is not the video title. Thumbnails are read in under a second, next to the title, which YouTube shows anyway.
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.
- 4d ago First seen · 178 lines · 13 tokens per session scan A 7024351bf8c3
thumbnail is a command published in the GitHub repository digitalsamba/claude-code-video-toolkit (2,256 stars, last pushed 4d ago), licensed MIT. It adds 13 tokens to every session and 1,891 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-13.
Other commands, from other repositories
playwright-test-generate
Generate tests for the test plan's bullet 1. Adding Todos. Generate one test at a time, never in parallel.
playwright-test-coverage
Produce test coverage.
qawolf-cli
Manage QA Wolf through the qawolf CLI. Use when asked to create, update, or list coverage requests, bug reports, or maintenance reports; start a run of flows or tags on the QA Wolf platform or read a run's results; list, set, or delete environment variables; manage environments, flows, or tags; run or list flows…
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.