Ltx2SAFE
AI-native video production toolkit for Claude Code
Overview
AI-native video production toolkit for Claude Code
87c47b18fb07OBSERVED · 2026-10-09Install
Commands as the repository documents them. They are shown, not run.
uv run tools/ltx2.py --prompt "A sunset over the ocean, golden light on waves, cinematic" --output sunset.mp4
uv run tools/ltx2.py --prompt "Gentle camera drift, soft ambient motion" --input photo.jpg --output animated.mp4
uv run tools/ltx2.py --prompt "..." --width 1024 --height 576 --num-frames 161 --output wide.mp4
uv run tools/ltx2.py --prompt "..." --quality fast --output quick.mp4
uv run tools/ltx2.py --prompt "..." --seed 42 --output reproducible.mp4
uv run tools/ltx2.py --lora crt-terminal \
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: ltx2 description: AI video generation with LTX-2.3 22B — text-to-video, image-to-video clips for video production. Use when generating video clips, animating images, creating b-roll, animated backgrounds, or motion content. Triggers include video generation, animate image, b-roll, motion, video clip, text-to-video, image-to-video. --- # 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`. ## Quick Reference ```bash # 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 forces a pipeline rebuild (~60s one-time cost per container lifetime per switch). ### `crt-terminal` — CRT / pixel-art terminals Base: LTX-2.3 22B, trained by [@lovis93](https://huggingface.co/lovis93/crt-animation-terminal-ltx-2.3-lora) (Apache 2.0). ```bash # Trigger word is auto-prepended — write the prompt normally uv run tools/ltx2.py --lora crt-terminal \ --prompt "a terminal typing out \"\\$ claude --continue\" character by character in glowing green pixel font, scanlines, phosphor glow, low choppy frame rate, hacker mood" \ --output crt_claude.mp4 ``` **What the preset changes:** - Prepends `crtanim,` to the prompt (the LoRA's trigger word) - Defaults to 1024×1024, 121 frames (the ratio it was trained on) - Relaxes the default negative prompt so on-screen text isn't filtered out **Prompt pattern:** `<CRT aesthetic> → <color palette> → <animation style> → <subject> → <literal text in quotes> → <mood>`. Keep on-screen text to 1–3 words — the model can't render long strings reliably. The LoRA prefers static framing; ask for camera moves explicitly if you want them. ## Valid Frame Counts `(n - 1) % 8 == 0`: 25 (~1s), 49 (~2s), 73 (~3s), 97 (~4s), **121 (~5s default)**, 161 (~6.7s), 193 (~8s max practical). ## Common Resolutions | Resolution | Ratio | Notes | |------------|-------|-------| | 768x512 | 3:2 | Default, good balance | | 512x512 | 1:1 | Square, fastest | | 1024x576 | 16:9 | Widescreen | | 576x1024 | 9:16 | Portrait/vertical | ## Prompting Guide LTX-2 responds well to cinematographic descriptions. Layer these dimensions: - **Camera:** "Slow dolly forward", "Aerial drone shot", "Tracking shot", "Static wide angle" - **Lighting:** "Golden hour", "Cinematic lighting", "Neon-lit", "Soft diffused light" - **Motion:** "Timelapse of...", "Slow motion", "Gentle camera drift", "Gradually transitions" - **Style:** "Shot on 35mm film", "Documentary style", "Clean minimal aesthetic" - **Negative:** Always implicitly avoids "worst quality, blurry, jittery, watermark, text, logo" Keep prompts under 200 words. Be specific about the scene. ### Good Prompts ``` # Atmospheric b-roll "Aerial drone shot slowly flying over turquoise ocean waves breaking on white sand, golden hour sunlight, cinematic" # Product/tech scene "Close-up of hands typing on a mechanical keyboard, shallow depth of field, soft desk lamp lighting, cozy atmosphere" # Abstract background "Dark moody abstract background with flowing blue light streaks, subtle geometric grid, bokeh particles floating, cinematic tech atmosphere" # Animate a portrait "Professional headshot, subtle natural head movement, confident warm expression, studio lighting, shallow depth of field" # Animate a slide/screenshot "Gentle subtle particle effects floating across a presentation slide, soft ambient light shifts, very slight camera drift" ``` ### Bad Prompts ``` # Too vague "A cool video" # Too many competing ideas "A cat riding a skateboard while juggling fire on the moon during a thunderstorm" # Describing text/UI (model can't render text reliably) "A website showing the text 'Welcome to our platform'" ``` ## Video Production Use Cases ### B-Roll Clips Generate atmospheric 5s shots for cutaways between narrated scenes: ```bash uv run tools/ltx2.py --prompt "Futuristic holographic interface, glowing data visualizations, clean workspace, cinematic" --output broll_tech.mp4 uv run tools/ltx2.py --prompt "Aerial view of European city at golden hour, modern architecture" --output broll_europe.mp4 ``` ### Animated Slide Backgrounds Feed a slide screenshot and add subtle motion: ```bash uv run tools/ltx2.py --prompt "Gentle particle effects, soft ambient light shifts, very slight camera drift" --input slide.png --output animated_slide.mp4 ``` ### Animated Portraits Bring still headshots to life: ```bash uv run tools/ltx2.py --prompt "Subtle natural head movem
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
87c47b18fb07full audit observations/trust-audit/skill/digitalsamba__ltx2.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-09 | 87c47b18fb07 | SAFE | B | 89 | first audit |
Questions
What does the Ltx2 skill do?
AI-native video production toolkit for Claude Code
Is Ltx2 safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Ltx2 access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (87c47b18fb07), read on 2026-10-09. The repository is watched, and a new audit runs when it changes — this is the first audit.