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 SupercmoHQ/superCMO-skills --skill cloning-video-adsgit clone --depth 1 https://github.com/SupercmoHQ/superCMO-skillsWrote 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/supercmohq/supercmo-skills/cloning-video-ads)<a href="https://agentmods.dev/skills/supercmohq/supercmo-skills/cloning-video-ads"><img src="https://agentmods.dev/badge/skills/supercmohq/supercmo-skills/cloning-video-ads/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/supercmohq/supercmo-skills/cloning-video-ads"><img src="https://agentmods.dev/badge/skills/supercmohq/supercmo-skills/cloning-video-ads.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 | $0.00117 | $0.02762 |
| Opus 5.5 | $0.00047 | $0.01105 |
| Sonnet 5.5 | $0.00023 | $0.00552 |
| Haiku 4.5 | $0.00012 | $0.00276 |
Grade A, and why
cloning-video-ads 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cloning video ads
Take a video ad the user likes and rebuild it with the user's own product. The reference ad's structure, pacing, shots and hook are kept; its product, brand and spoken lines are replaced with the user's.
A product ad built from scratch, with no reference video to follow, is out of scope — that belongs to generating-ad-videos. A still image ad belongs to generating-image-ads.
Workflow
Step 1: Analyze the reference ad
The reference ad is the plan the clone is rebuilt from, so read it first and read it in full — a thin read here is the one thing that breaks the clone, and no later step recovers it.
Read references/reading-the-ad.md for exactly what to pull out and the breakdown format, then run video_analysis on the ad (a video file or URL) to produce that timed, second-by-second breakdown of the whole thing.
- No reference ad → there is nothing to read yet. Don't invent one; it becomes the first thing the interview (Step 3) asks for.
Step 2: Read the product
- A product image or URL — the user's product, the one that replaces the original's → hand it to
analyzing-productsfor what the product is, how a person physically uses it, which parts open or move, and what must stay identical wherever it appears. - Run
image_analysison every other image supplied — what each one shows. The product photo is already covered byanalyzing-products; don't read it twice. - No product → don't guess at one. It becomes the first thing the interview (Step 3) asks for.
Step 3: Interview
Skip this when you already have both the reference ad and the product, and the user hasn't asked to change the length or ratio.
Otherwise ask once, bundled into a single message, always with a free-text way out.
| Ask | When |
|---|---|
| The reference ad — the video to clone | It wasn't supplied. Offer to wait for an upload or a link. |
| The product — a link or a photo | Neither was supplied. Offer to wait for an upload; a photographed product beats a described one. |
| How long | Only if the user wants a length other than the reference ad's. The default is to match it. |
| Aspect ratio | Only if the user wants a ratio other than the reference ad's. The default is to match it. |
What ships with it
3 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.
- 1mo ago First seen · 135 lines · 117 tokens per session scan A 329646676931
cloning-video-ads is a skill published in the GitHub repository SupercmoHQ/superCMO-skills (242 stars, last pushed 6d ago), licensed Apache-2.0. It adds 117 tokens to every session and 2,762 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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