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 explainer-videogit 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/explainer-video)<a href="https://agentmods.dev/skills/2233admin/design-pipeline/explainer-video"><img src="https://agentmods.dev/badge/skills/2233admin/design-pipeline/explainer-video/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/explainer-video"><img src="https://agentmods.dev/badge/skills/2233admin/design-pipeline/explainer-video.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 | $0.00092 | $0.02519 |
| Opus 5 | $0.00046 | $0.01260 |
| Sonnet 5 | $0.00018 | $0.00504 |
| Haiku 4.5 | $0.00009 | $0.00252 |
Grade A, and why
explainer-video 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 5d 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 explainer-video — 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explainer Video
Turn one message into a paced, narrated 30–90s short. Run the full pipeline: script → storyboard → scene build → narration/caption sync → edit → polish, with a consistent style system throughout.
When to use
- Produce a 30–90s product, how-it-works, onboarding, or concept video.
- Go from a raw idea or feature to a script, storyboard, and assembled piece.
- Sync narration to visuals and add captions for muted playback.
Story structure (decide this first)
An explainer is an argument, not a feature tour. Before any pipeline step, lock the narrative so every later choice serves it.
- One core idea. A single sentence the viewer should be able to repeat afterward. If you can't state it in one line, the video has no spine — cut scope until you can. Everything that doesn't serve that idea gets dropped, not shrunk.
- Script-first. The VO is the spine; visuals illustrate the line being spoken, never lead it. Write and time the words before you storyboard or animate — it is far cheaper to cut a sentence than a built scene.
- Earn the "how" with stakes. Don't jump from problem to mechanism. Make the viewer feel the cost of the problem first; that tension is what makes them watch the solution.
The explainer story arc — a beat per stage, in order:
| Stage | Narrative job | What the viewer should think |
|---|---|---|
| Problem | Name the pain in their words | "That's me." |
| Stakes | Show what the pain costs (time, money, risk) | "I need this fixed." |
| Solution | Introduce the product/idea as the fix, in one line | "Oh — that solves it." |
| How it works | The mechanism in 1–3 concrete steps | "I get how it does that." |
| Payoff / CTA | The after-state + one next action | "I want that. I'll do X." |
(The Script formula table below maps these stages to runtime shares and word budgets — this section is the why and order; that one is the how long.)
Pick one analogy and ride it
Abstract mechanisms land when mapped to something the viewer already knows. Choose a single metaphor and keep it consistent across scenes — switching analogies mid-video resets comprehension.
What ships with it
2 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.
- 5d ago First seen · 181 lines · 92 tokens per session scan A d1c0e3147550
explainer-video is a skill published in the GitHub repository 2233admin/design-pipeline (9 stars, last pushed 6d ago), licensed MIT. It adds 92 tokens to every session and 2,519 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 explainer-video, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
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omd-apply
A skill that applies a project's DESIGN.md file as visual and brand guidance for interface work. It covers components, colors, fonts, layout, copy, motion, and visual assets.
ss-review
Review UI code for design system compliance, accessibility, and best practices.
ss-pattern
Generate a composed UI pattern from the active StyleSeed grammar and brand recipe using existing primitives.
ss-reference
Compile screenshots, URLs, Figma exports, or an existing UI into a project-local StyleSeed output grammar with evidence, tokens, confidence, anti-patterns, and a validation screen. Use when the user supplies a design reference that StyleSeed does not already model.
cicd-integration
Generate CI/CD pipeline configurations that automate design system quality checks — token validation, component linting, visual regression, accessibility scanning, and release gating. Produces ready-to-use pipeline files for GitHub Actions, GitLab CI, CircleCI, or Bitbucket Pipelines, configured to enforce the…