Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add notque/vexjoy-agent --skill image-to-videogit clone --depth 1 https://github.com/notque/vexjoy-agentWrote 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/notque/vexjoy-agent/image-to-video)<a href="https://agentmods.dev/skills/notque/vexjoy-agent/image-to-video"><img src="https://agentmods.dev/badge/skills/notque/vexjoy-agent/image-to-video/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/notque/vexjoy-agent/image-to-video"><img src="https://agentmods.dev/badge/skills/notque/vexjoy-agent/image-to-video.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
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 →
- medium Privilege Escalation · line 170 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
- medium Privilege Escalation · line 185 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
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 | $0.00014 | $0.00867 |
| Opus 5.5 | $0.00006 | $0.00347 |
| Sonnet 5.5 | $0.00003 | $0.00173 |
| Haiku 4.5 | $0.00001 | $0.00087 |
Grade A, and why
image-to-video 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 25d 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image to Video Skill
Combine a static image with an audio file to produce an MP4 via FFmpeg. Supports resolution presets, audio visualization overlays, and batch processing. For image generation, use image-gen.
Deep References
| Signal | Load | Why |
|---|---|---|
| FFmpeg filter graphs for visualization modes | references/ffmpeg-filters.md |
Scale/pad, showwaves, showspectrum, overlay filters |
Phase 1: VALIDATE
- Check FFmpeg:
ffmpeg -version. If missing, stop with install instructions. - Verify both input files exist with absolute paths and non-zero size. Supported: PNG/JPG/JPEG/GIF/WEBP/BMP (image), MP3/WAV/M4A/OGG/FLAC (audio).
- Determine parameters from the user's request -- do not default to static when the user requested a visualization.
| Preset | Dimensions | Platform |
|---|---|---|
1080p |
1920x1080 | YouTube HD (default) |
720p |
1280x720 | Standard HD |
square |
1080x1080 | Instagram, social |
vertical |
1080x1920 | Stories, Reels, TikTok |
Visualization modes (off unless requested): waveform, spectrum, cqt, bars.
Gate: FFmpeg installed, both files exist, parameters resolved.
Phase 2: PREPARE
Use the user's output path or derive from audio filename (/same/dir/filename.mp4). Verify directory is writable.
Phase 3: ENCODE
Defaults: libx264 preset medium, CRF 23, yuv420p, 192k AAC.
python3 $HOME/vexjoy-agent/skills/content/image-to-video/scripts/image_to_video.py \
--image /path/to/image.png --audio /path/to/audio.mp3 \
--output /path/to/output.mp4 --resolution 1080p --visualization static
Batch mode (matched pairs in workspace/input/):
python3 $HOME/vexjoy-agent/skills/content/image-to-video/scripts/image_to_video.py \
--process-workspace --visualization waveform
Gate: Script exits 0.
Phase 4: VERIFY
FFmpeg can exit 0 but produce a corrupt file. Always probe:
ffprobe -v error -show_entries format=duration,size -show_entries stream=codec_name,width,height \
-of default=noprint_wrappers=1 /path/to/output.mp4
What ships with it
6 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.
- 26d ago Changed · -48 lines · +14 tokens per session 302d19b53ad4
- 27d ago Changed · -98 lines scan B → A 2857df3fd9cb
- 1mo ago First seen · 199 lines · 14 tokens per session scan B be695c9f9e36
image-to-video is a skill published in the GitHub repository notque/vexjoy-agent (442 stars, last pushed today), licensed MIT. It adds 14 tokens to every session and 867 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 2026-09-03.
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