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 skills/digitalsamba/claude-code-video-toolkit/ideogram4Wrote 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/skills/digitalsamba/claude-code-video-toolkit/ideogram4)<a href="https://agentmods.dev/skills/digitalsamba/claude-code-video-toolkit/ideogram4"><img src="https://agentmods.dev/badge/skills/digitalsamba/claude-code-video-toolkit/ideogram4/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/skills/digitalsamba/claude-code-video-toolkit/ideogram4"><img src="https://agentmods.dev/badge/skills/digitalsamba/claude-code-video-toolkit/ideogram4.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00099 | $0.02003 |
| Opus 5.5 | $0.00040 | $0.00801 |
| Sonnet 5.5 | $0.00020 | $0.00401 |
| Haiku 4.5 | $0.00010 | $0.00200 |
Grade A, and why
ideogram4 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ideogram 4 Skill
Text-to-image generation with Ideogram 4 (9.3B, open-weight, released June 2026). Its superpower is best-in-class in-image text rendering — it beats much larger models (FLUX.2 dev 32B, Qwen-Image 20B, Hunyuan 80B) at rendering legible signage, logos, captions, and multi-line text — plus exact color-palette and bounding-box control.
That advantage is locked behind a structured JSON caption format. A plain-text prompt gets you FLUX-level results and misses the entire point of using this model. This skill teaches Claude to act as the "magic prompt" expander — turning a user's casual request into the JSON caption Ideogram 4 was trained on.
Backend: The toolkit uses Ideogram's hosted v4 API (not self-hosted weights). The API accepts a structured
json_prompt, so everything this skill teaches applies directly — Claude builds the caption, the tool posts it asjson_prompt. Paid API plans include a commercial license, which the self-hostable weights (non-commercial) do not — that's why we use the API. Cost is ~$0.03/image (turbo) to ~$0.10/image (quality).
When to Use This Skill
Reach for Ideogram 4 (over FLUX.2) when the image needs:
- Legible on-image text — title cards, thumbnails, lower-thirds backgrounds, signage, logos, quote cards, CTAs with a headline baked in
- Exact brand colors — hex color-palette conditioning, per-element
- Controlled layout — bounding boxes place text/objects in specific regions
- Multilingual text in the image
Use FLUX.2 instead when: the image has no critical text, you need commercial-licensed output,
or you just want a fast atmospheric background. FLUX takes plain natural-language prompts; Ideogram
wants JSON. See tools/flux2.py.
The One Thing to Get Right
Always emit a structured JSON caption, not a plain sentence. The model is trained exclusively on JSON captions that name every element explicitly. Claude is a better expander than Ideogram's free hosted magic-prompt (their own docs note the shipped one "is not the same used in production"), so build the caption yourself using this skill rather than passing raw text.
What ships with it
2 files 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.
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 Changed · +37 lines 81e5bced9c53
- 1mo ago First seen · 94 lines · 99 tokens per session scan A 738a025f66b0
ideogram4 is a skill published in the GitHub repository digitalsamba/claude-code-video-toolkit (2,256 stars, last pushed 4d ago), licensed MIT. It adds 99 tokens to every session and 2,003 once invoked, about $0.0004 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 2026-08-30.
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