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 image-ad-clonegit 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/image-ad-clone)<a href="https://agentmods.dev/skills/krusemediallc/arcads-claude-code/image-ad-clone"><img src="https://agentmods.dev/badge/skills/krusemediallc/arcads-claude-code/image-ad-clone/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/image-ad-clone"><img src="https://agentmods.dev/badge/skills/krusemediallc/arcads-claude-code/image-ad-clone.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00124 | $0.02408 |
| Opus 5.5 | $0.00050 | $0.00963 |
| Sonnet 5.5 | $0.00025 | $0.00482 |
| Haiku 4.5 | $0.00012 | $0.00241 |
Grade A, and why
image-ad-clone 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:
- image-ad-clone — 100% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
image-ad-clone (Arcads)
Take an existing image ad and turn it into a reusable, parameterizable prompt template that gets appended to the shared 37-template image-ad library. The template is validated by round-tripping through one of the Arcads image-ad generators — ChatGPT Image 2 (typography / UI-mimicry templates) or Nano Banana (photoreal / lifestyle / multi-reference templates).
This skill replaces the older Uni1-locked image-ad-clone (which only worked with Luma uni-1). It's backend-agnostic: at Phase 1 the agent asks you (or auto-detects from the reference) whether to validate against gpt-image-2 or Nano Banana, then routes through the matching generator script in this repo.
Read order
- This file — Arcads-specific generator paths, model-choice decision, what's locked at the per-repo layer.
- shared/skills/image-ad-clone/prompting/guide.md — the full model-agnostic 10-phase workflow (visual analysis → draft prompt → generate-with-reference → iterate → generalize → test → cross-model validate → document → save).
- shared/skills/image-ad-prompting/prompting/template-format.md — entry skeleton.
- shared/skills/image-ad-prompting/prompting/prompt-library.md — destination for the new entry. 37 validated templates already there; new entries go at T40+.
Hard rules
Inherits all 6 hard rules from the shared guide (strip platform chrome, validate by generating, test the generalized version, no brand-specific text in the final template, never silently overwrite, document model notes for both backends). Plus per-repo:
- Backend is one of: ChatGPT Image 2 OR Nano Banana on Arcads. Never uni-1. The script choice happens in Phase 1 once the user picks (or the agent auto-detects).
Picking the right backend in Phase 1
Pick by what the reference ad is showing — most templates fall into one clear bucket.
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 · 133 lines · 124 tokens per session scan A 3804db13ef4e
image-ad-clone is a skill published in the GitHub repository krusemediallc/arcads-claude-code (1,625 stars, last pushed 5d ago), licensed MIT. It adds 124 tokens to every session and 2,408 once invoked, about $0.0005 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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