Arcads AI Video is an agent skill pack and prompting workspace for creating marketing videos and images through an Arcads account. Claude Code and Cursor users use it to produce advertising creative with Arcads' video, image, audio, and template tools. The catalogue entries provide the skills, instructions, hook, setting, and rule that support this workflow.
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 krusemediallc/arcads-claude-code --skill clone-adgit clone --depth 1 https://github.com/krusemediallc/arcads-claude-codeWrote 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/krusemediallc/arcads-claude-code/clone-ad)<a href="https://agentmods.dev/skills/krusemediallc/arcads-claude-code/clone-ad"><img src="https://agentmods.dev/badge/skills/krusemediallc/arcads-claude-code/clone-ad/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/krusemediallc/arcads-claude-code/clone-ad"><img src="https://agentmods.dev/badge/skills/krusemediallc/arcads-claude-code/clone-ad.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Excessive Agency · line 310 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00112 | $0.05514 |
| Opus 5.5 | $0.00045 | $0.02206 |
| Sonnet 5.5 | $0.00022 | $0.01103 |
| Haiku 4.5 | $0.00011 | $0.00551 |
Grade A, and why
clone-ad 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- clone-ad — 92% identical, 22 lines differ
How it starts
The opening of the file, as written. The whole thing — 469 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clone ad — Seedance 2.0
Clone an existing video ad for a different product or offer. The agent analyzes the source video frame-by-frame, transcribes dialogue, extracts the visual style and beat structure, then generates a new Seedance 2.0 video adapted for the user's product.
How this differs from analyze-video:
- analyze-video → output is a reusable markdown template saved to
prompt-library/ - clone-ad → output is a generated Seedance 2.0 video delivered to the user
Prerequisites
Before starting, verify:
which ffmpeg || echo "MISSING — run: brew install ffmpeg"
python3 -c "import whisper; print('whisper OK')" 2>/dev/null || echo "MISSING — run: pip3 install openai-whisper"
Both extract-frames.sh and whisper depend on ffmpeg. If missing, install via brew install ffmpeg before proceeding.
Workflow
Step 0: Gather inputs
Collect from the user:
| Input | Required | Notes |
|---|---|---|
| Source video | yes | The video ad to clone. File path to .mp4, .mov, .webm |
| Product image | recommended | Reference photo of the user's product. Becomes referenceImages / @(img1) in the prompt. Without this, Seedance invents its own product design. |
| Product/offer description | if no image | Text description of the product, its features, target audience, and key selling points. Used to rewrite dialogue and product references. |
| Brand voice | optional | Check MASTER_CONTEXT.md for brand blocks. If empty, ask the user for tone/audience preferences. |
If the user only provides a video and says "clone this for my product," ask them for at least a product image or a text description before proceeding.
Step 1: Extract frames and audio
Reuse the analyze-video extraction script — do NOT duplicate it.
bash "skills/arcads-external-api/prompting/analyze-video/scripts/extract-frames.sh" \
"<source_video_path>" "/tmp/clone-ad-analysis" <num_frames>
Frame count by duration:
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 · 469 lines · 112 tokens per session scan A 5fc53dc8b3a2
clone-ad is a skill published in the GitHub repository krusemediallc/arcads-claude-code (1,625 stars, last pushed 5d ago), licensed MIT. It adds 112 tokens to every session and 5,514 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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