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 generating-videosgit 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/generating-videos)<a href="https://agentmods.dev/skills/supercmohq/supercmo-skills/generating-videos"><img src="https://agentmods.dev/badge/skills/supercmohq/supercmo-skills/generating-videos/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/generating-videos"><img src="https://agentmods.dev/badge/skills/supercmohq/supercmo-skills/generating-videos.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 | $0.00139 | $0.01925 |
| Opus 5.5 | $0.00056 | $0.00770 |
| Sonnet 5.5 | $0.00028 | $0.00385 |
| Haiku 4.5 | $0.00014 | $0.00193 |
Grade A, and why
generating-videos 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Generation
Turn a brief into a video.
Workflow
Step 1: Read the brief and the media
Look at everything the user supplied. Run image_analysis on each image and video_analysis on
each video. Write down what each one shows — who is in it, where it is, how it is lit, how it is
framed — so the prompt matches it instead of describing something different. Send a product URL or
photo to analyzing-products. Skip an image you already know: you made it this turn, or you have
already analyzed it.
Then read the brief: how long the video runs, what happens in it, where it will be posted, and whether anyone speaks.
Where the video has a product, write one description of it and reuse it unchanged in every storyboard — rephrasing it between calls reads as a different product.
- Material and finish, surface by surface.
- Size — its width and height, and how it sits against a hand.
- Two to five visual anchors — features you can verify in the product image and nothing else: exact colours, the shape of a closure or handle, the gauge of a chain or strap, a surface finish, a distinguishing mark.
- What may be done with each part — which parts are fixed to it, and the whole of what the moving ones allow. Nothing later does anything to the product that isn't on this list.
Don't transcribe what the label says. Spelling out the printing invites the model to redraw it, and redrawn text comes back warped.
Step 2: Pick the model and load its parameters
seedance-2.0-fast is the default — the general-purpose workhorse; a weak result is usually the
prompt's fault, not the model's.
The storyboard route always runs on seedance-2.0-fast unless the user named a model. The table below
decides a single clip.
Reach past the default only on a clear signal:
| Reach for another model when the brief… | Model |
|---|---|
| Needs one unbroken shot longer than 15 seconds, or more than nine reference images | seedance-2.5 |
| Needs spoken dialogue with lip-sync, the tightest prompt-following, or top cinematic quality | veo-3.1-fast |
| Is editing an existing clip — restyle it, add or replace an element, fix on-screen text — or hinges on legible on-screen text | gemini-omni |
| Must hold one person or character consistent across references or several shots | kling-3.0-pro |
| Has an edgy or sensitive subject Seedance would refuse, or wants the fastest, cheapest draft | grok-imagine-video |
| Is a high-volume or cost-sensitive batch where top quality isn't essential | wan-2.7 |
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 · 126 lines · 139 tokens per session scan A bc1a8b1a30e7
generating-videos is a skill published in the GitHub repository SupercmoHQ/superCMO-skills (242 stars, last pushed 6d ago), licensed Apache-2.0. It adds 139 tokens to every session and 1,925 once invoked, about $0.0006 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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