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 oyi77/1ai-skills --skill frontend-designgit clone --depth 1 https://github.com/oyi77/1ai-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/oyi77/1ai-skills/frontend-design)<a href="https://agentmods.dev/skills/oyi77/1ai-skills/frontend-design"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/frontend-design/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/oyi77/1ai-skills/frontend-design"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/frontend-design.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 | $0.00039 | $0.01250 |
| Opus 5 | $0.00019 | $0.00625 |
| Sonnet 5 | $0.00008 | $0.00250 |
| Haiku 4.5 | $0.00004 | $0.00125 |
Grade A, and why
frontend-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 8d 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Frontend design skill for building beautiful, consistent UIs. Covers design systems, Tailwind CSS, component patterns, spacing, typography, color theory, and responsive design.
Capabilities
- Build design systems with reusable component patterns
- Master Tailwind CSS utilities and custom configurations
- Apply visual hierarchy, spacing, and typography principles
- Create responsive layouts with mobile-first approach
- Implement dark mode and theme switching
When to Use
Trigger phrases:
-
"frontend design"
-
"Design system patterns — component architecture, Tailwind mastery, visual hierar"
-
Starting a new frontend project and need design system
-
Existing UI looks inconsistent or unprofessional
-
Need to implement responsive design across devices
-
Building component library for team reuse
When NOT to Use
- Task is about content strategy, not creation (use strategy skills)
- Task is about content distribution (use distribution skills)
- You need to analyze content performance (use analytics skills)
- Task is about content moderation (use moderation tools)
- You don't have content guidelines
- Task requires domain expertise (consult experts)
Pseudo Code
The frontend-design workflow follows a standard pipeline pattern.
Core flow:
# frontend-design primary flow
input = prepare(raw_data)
result = process(input, config={architecture, component, design, frontend, hierarchy})
validate(result)
deliver(result)
Error handling:
on error:
log(error_details)
retry_with_backoff(max=3)
if still_failing: alert_and_escalate()
Core Workflow
# frontend-design primary flow
input = prepare(raw_data)
result = process(input, config={architecture, component, design, frontend, hierarchy})
validate(result)
deliver(result)
Error Handling
on error:
log(error_details)
retry_with_backoff(max=3)
if still_failing: alert_and_escalate()
Design Token System
// tailwind.config.js
module.exports = {
theme: {
extend: {
colors: {
primary: { 50: '#eff6ff', 500: '#3b82f6', 900: '#1e3a8a' },
neutral: { 50: '#fafafa', 500: '#737373', 900: '#171717' }
},
spacing: { '18': '4.5rem', '88': '22rem' },
fontSize: { 'display': ['3rem', { lineHeight: '1.2', fontWeight: '700' }] }
}
}
}
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.
- 8d ago First seen · 172 lines · 39 tokens per session scan A 3930a040d9a1
frontend-design is a skill published in the GitHub repository oyi77/1ai-skills (12 stars, last pushed today), licensed MIT. It adds 39 tokens to every session and 1,250 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 2026-09-03.
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