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 2233admin/design-pipeline --skill video-to-superpromptgit clone --depth 1 https://github.com/2233admin/design-pipelineWrote 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/2233admin/design-pipeline/video-to-superprompt)<a href="https://agentmods.dev/skills/2233admin/design-pipeline/video-to-superprompt"><img src="https://agentmods.dev/badge/skills/2233admin/design-pipeline/video-to-superprompt/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/2233admin/design-pipeline/video-to-superprompt"><img src="https://agentmods.dev/badge/skills/2233admin/design-pipeline/video-to-superprompt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00090 | $0.01173 |
| Opus 5 | $0.00045 | $0.00587 |
| Sonnet 5 | $0.00018 | $0.00235 |
| Haiku 4.5 | $0.00009 | $0.00117 |
Grade A, and why
video-to-superprompt 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 7d 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.
This is a copy
100% identical to video-to-superprompt — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video To Superprompt
Goal
Convert any usable reference video into a builder-ready prompt that captures what the video shows, how it moves, how it should be rebuilt, and what assets or generated media are needed. The default output is one paste-ready prompt unless the user asks for an article, asset pack, or implementation.
Workflow
-
Locate the source video.
- Accept local paths, uploaded files, URLs, browser-visible videos, article assets, or repo media.
- If the video is referenced but inaccessible, ask for the exact file or URL before inventing details.
- If the user wants exact recreation, inspect any source HTML/CSS/JS or local page connected to the video before writing the prompt.
-
Inspect the video technically.
- For local files, run
ffprobefor duration, dimensions, frame rate, codec, and size. - Extract representative frames with
ffmpeg, favoring timeline beats over uniform thumbnails. - Suggested quick pass:
ffprobe -v error -show_entries format=duration,size:stream=width,height,r_frame_rate -of json "$VIDEO" mkdir -p /tmp/video-frames ffmpeg -y -i "$VIDEO" -vf fps=1 /tmp/video-frames/frame-%03d.jpg - For long or scroll-heavy videos, also extract start/middle/end and visible transition moments.
- For local files, run
-
Analyze in layers.
- Story: page/app purpose, emotional arc, section order, transition between beats.
- Screen/layout: viewport framing, grids, sticky zones, cards, media, overlays, margins, navigation, footer.
- Motion: reveal timing, easing, parallax, masks, pinned sections, scroll scrubbing, hover/tap states, looped ambient motion, camera moves.
- Visual design: typography, color palette, surfaces, borders, shadows, texture, iconography, image/video treatment.
- Technical rebuild: CSS/native APIs, IntersectionObserver, Web Animations API, GSAP ScrollTrigger, Lenis, Framer Motion/Motion One, Three.js/WebGL, canvas, video currentTime scrubbing, carousels, or other domain libraries.
- Accessibility/performance: reduced motion, mobile behavior, touch/keyboard states, lazy loading, video preload, pixel-ratio caps, static fallbacks.
What ships with it
7 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.
- 7d ago First seen · 73 lines · 90 tokens per session scan A 2b0db0096fb7
video-to-superprompt is a skill published in the GitHub repository 2233admin/design-pipeline (9 stars, last pushed 8d ago), licensed MIT. It adds 90 tokens to every session and 1,173 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to video-to-superprompt, differing in 0 lines, and is treated as a copy.
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