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/runpodWrote 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/runpod)<a href="https://agentmods.dev/skills/digitalsamba/claude-code-video-toolkit/runpod"><img src="https://agentmods.dev/badge/skills/digitalsamba/claude-code-video-toolkit/runpod/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/runpod"><img src="https://agentmods.dev/badge/skills/digitalsamba/claude-code-video-toolkit/runpod.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 4 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 14 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 15 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.
- medium Data Exfiltration · line 92 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 93 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00064 | $0.02358 |
| Opus 5.5 | $0.00026 | $0.00943 |
| Sonnet 5.5 | $0.00013 | $0.00472 |
| Haiku 4.5 | $0.00006 | $0.00236 |
Grade A, and why
runpod 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 1mo 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 — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RunPod Cloud GPU
Run open-source AI models on cloud GPUs via RunPod serverless. Pay-per-second, no minimums.
Setup
# 1. Create account at https://runpod.io
# 2. Add API key to .env
echo "RUNPOD_API_KEY=your_key_here" >> .env
# 3. Deploy any tool with --setup
uv run tools/image_edit.py --setup
uv run tools/upscale.py --setup
uv run tools/dewatermark.py --setup
uv run tools/sadtalker.py --setup
uv run tools/qwen3_tts.py --setup
Each --setup command:
- Creates a RunPod template from the Docker image
- Creates a serverless endpoint with appropriate GPU
- Saves the endpoint ID to
.env(e.g.RUNPOD_QWEN_EDIT_ENDPOINT_ID)
Available Images
All images are public on GHCR — no authentication needed.
| Tool | Docker Image | GPU | VRAM | Typical Cost |
|---|---|---|---|---|
| image_edit | ghcr.io/conalmullan/video-toolkit-qwen-edit:latest |
A6000/L40S | 48GB+ | ~$0.05-0.15/job |
| upscale | ghcr.io/conalmullan/video-toolkit-realesrgan:latest |
RTX 3090/4090 | 24GB | ~$0.01-0.05/job |
| dewatermark | ghcr.io/conalmullan/video-toolkit-propainter:latest |
RTX 3090/4090 | 24GB | ~$0.05-0.30/job |
| sadtalker | ghcr.io/conalmullan/video-toolkit-sadtalker:latest |
RTX 4090 | 24GB | ~$0.05-0.15/job |
| qwen3_tts | ghcr.io/conalmullan/video-toolkit-qwen3-tts:latest |
ADA 24GB | 24GB | ~$0.01-0.05/job |
Total monthly cost: Rarely exceeds $10 even with heavy use.
How It Works
All tools follow the same pattern:
Local CLI → Upload input to cloud storage → RunPod API → Poll for result → Download output
- File transfer: Tools use Cloudflare R2 when configured (
R2_ACCOUNT_ID,R2_ACCESS_KEY_ID,R2_SECRET_ACCESS_KEY,R2_BUCKET_NAME), falling back to free upload services - RunPod API: Tools call the
/runendpoint, then poll/status/{job_id}until complete - Cold vs warm start: First request after idle spins up a worker (~30-90s). Subsequent requests are fast (~5-15s)
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.
- 1mo ago First seen · 233 lines · 64 tokens per session scan A a61ea498acd0
runpod is a skill published in the GitHub repository digitalsamba/claude-code-video-toolkit (2,281 stars, last pushed today), licensed MIT. It adds 64 tokens to every session and 2,358 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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