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 agentmods add skills/artttj/rapid-stack/designnpx skills add artttj/rapid-stack --skill designgit clone --depth 1 https://github.com/artttj/rapid-stackWhat 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 | $0.00034 | $0.02286 |
| Opus 5 | $0.00017 | $0.01143 |
| Sonnet 5 | $0.00007 | $0.00457 |
| Haiku 4.5 | $0.00003 | $0.00229 |
Grade A, and why
design 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 2d 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Principles
Core philosophy: Every interface should look designed by a team that obsesses over 1-pixel differences. Not stripped, crafted. And designed for its specific context.
Avoid AI Sameness
AI-generated UIs have a recognizable "median of the internet" feel. Polished but generic, like everything was designed by the same committee. Break out of that by making deliberate choices instead of reaching for defaults.
AI default patterns to actively avoid:
| AI default | Why it happens | Do this instead |
|---|---|---|
| Indigo/purple gradients | Tailwind's bg-indigo-500 saturated training data |
Choose an accent color that fits the product's emotional job |
| Inter or system fonts everywhere | Statistically safest choice | Pick typography that matches the product personality (see Choose Typography below) |
| Three-column icon grid | Every SaaS landing page template uses this | Vary card layouts by content type. Metric cards, feature cards, and testimonial cards should look different from each other |
| Centered hero + CTA button | The default starting point for every landing page | Consider what the user actually needs first. Maybe it's a dense dashboard, a split layout, or content-forward with no hero at all |
| Uniform border-radius on everything | rounded-lg applied without thinking |
Pick a radius system and vary it by component role (sharp for data, softer for interactive) |
| White/light gray background + subtle shadow cards | The safest possible surface treatment | Commit to a depth strategy that matches the product (see Depth Strategy below) |
| Decorative gradients on hero sections | Looks "modern" without communicating anything | If using gradients, make them functional (show hierarchy, direct attention) not decorative |
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.
- 2d ago First seen · 204 lines · 34 tokens per session scan A 47c83007bc96
design is a skill published in the GitHub repository artttj/rapid-stack (2 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 2,286 once invoked, about $0.0002 per session on Opus 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 2026-08-31.
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