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/ltx2Wrote 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/ltx2)<a href="https://agentmods.dev/skills/digitalsamba/claude-code-video-toolkit/ltx2"><img src="https://agentmods.dev/badge/skills/digitalsamba/claude-code-video-toolkit/ltx2/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/ltx2"><img src="https://agentmods.dev/badge/skills/digitalsamba/claude-code-video-toolkit/ltx2.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 215 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 216 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00076 | $0.03191 |
| Opus 5.5 | $0.00030 | $0.01276 |
| Sonnet 5.5 | $0.00015 | $0.00638 |
| Haiku 4.5 | $0.00008 | $0.00319 |
Grade A, and why
ltx2 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 7d 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 — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LTX-2.3 Video Generation
Generate ~5 second video clips from text prompts or images using the LTX-2.3 22B DiT model.
Runs on Modal (A100-80GB). Requires MODAL_LTX2_ENDPOINT_URL in .env.
LTX-2.5 is a deploy-time opt-in on the same endpoint; see LTX-2.5 (opt-in).
Quick Reference
# Text-to-video
uv run tools/ltx2.py --prompt "A sunset over the ocean, golden light on waves, cinematic" --output sunset.mp4
# Image-to-video (animate a still image)
uv run tools/ltx2.py --prompt "Gentle camera drift, soft ambient motion" --input photo.jpg --output animated.mp4
# Custom resolution and duration
uv run tools/ltx2.py --prompt "..." --width 1024 --height 576 --num-frames 161 --output wide.mp4
# Fast mode (fewer steps, quicker)
uv run tools/ltx2.py --prompt "..." --quality fast --output quick.mp4
# Reproducible output
uv run tools/ltx2.py --prompt "..." --seed 42 --output reproducible.mp4
Parameters
| Parameter | Default | Description |
|---|---|---|
--prompt |
(required) | Text description of the video |
--input |
- | Input image for image-to-video |
--width |
768 | Video width (divisible by 64) |
--height |
512 | Video height (divisible by 64) |
--num-frames |
121 | Frame count, must satisfy (n-1) % 8 == 0 |
--fps |
24 | Frames per second |
--quality |
standard | standard (30 steps) or fast (15 steps) |
--steps |
30 | Override inference steps directly |
--seed |
random | Seed for reproducibility |
--output |
auto | Output file path |
--negative-prompt |
sensible default | What to avoid |
--lora |
none | Style LoRA preset. Currently: crt-terminal. |
Style LoRAs
Style LoRAs bias the output toward a specific visual aesthetic. They're baked into the Modal image and selected per-request; switching LoRAs rebuilds the server pipeline.
On an LTX2_VERSION=2.5 deployment: the presets below were trained on LTX-2.3. crt-terminal was checked on 2.5 (2026-10-12) and does not reproduce its CRT look there: it changes the output, but the result is a photoreal scene with green text. Use a 2.3 deployment for it. Keys that don't match are skipped without an error, so compare any other 2.3 LoRA with 2.3 before relying on it.
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.
- 7d ago Changed · +24 lines 2a07a8054d95
- 1mo ago First seen · 223 lines · 76 tokens per session scan A 0f8851a1a0b7
ltx2 is a skill published in the GitHub repository digitalsamba/claude-code-video-toolkit (2,281 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 3,191 once invoked, about $0.0003 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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