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 travisjneuman/.claude --skill frontend-enhancergit clone --depth 1 https://github.com/travisjneuman/.claudeWrote 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/travisjneuman/.claude/frontend-enhancer)<a href="https://agentmods.dev/skills/travisjneuman/.claude/frontend-enhancer"><img src="https://agentmods.dev/badge/skills/travisjneuman/.claude/frontend-enhancer/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/travisjneuman/.claude/frontend-enhancer"><img src="https://agentmods.dev/badge/skills/travisjneuman/.claude/frontend-enhancer.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 | $0.00045 | $0.01475 |
| Opus 5.5 | $0.00018 | $0.00590 |
| Sonnet 5.5 | $0.00009 | $0.00295 |
| Haiku 4.5 | $0.00005 | $0.00147 |
Grade A, and why
frontend-enhancer 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 24d 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 — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Frontend Enhancer
Transform web applications into visually polished, human-designed experiences.
Prerequisite: Research First
For a new design direction, run ui-research first so choices come from real reference products rather than default styles; the specific defaults to avoid are under "Avoiding the AI Look". See UI Inspiration Sources.
When to Use
Use for:
- Improving styling and visual design
- Creating responsive layouts
- Adding animations and transitions
- Selecting color schemes
- Building modern UI patterns
- Enhancing aesthetics
Don't use when:
- Need inspiration first → use
ui-researchfirst - UX flow design → use
generic-ux-designer - Code architecture → use
generic-feature-developer - Code review → use
generic-code-reviewer
Foundational References:
- UI Inspiration Sources - Research sources
- Design Patterns - Visual tokens
Research-Driven Enhancement Workflow
- Research - Use
ui-researchskill first (5-10 examples minimum) - Assess - Identify current gaps against research findings
- Plan - Define direction based on inspiration analysis
- Foundation - Set up colors, spacing, animations in theme
- Apply - Implement with human polish (not defaults)
- Anti-AI Check - Verify no generic AI patterns
- Refine - Test responsiveness, verify accessibility
- Review - Check hierarchy, consistency, performance
Color Palette Selection
| Palette | Use Case |
|---|---|
| Corporate Blue | Business apps, SaaS |
| Vibrant Purple | Creative tools, portfolios |
| Minimalist Gray | Clean, sophisticated |
| Warm Sunset | Consumer apps, e-commerce |
| Ocean Fresh | Health, finance apps |
| Dark Mode | Developer tools, dashboards |
Each palette needs: Primary, Secondary, Accent, Background, Foreground, Muted, Success, Warning, Error
What ships with it
11 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.
- assets/animations.css 3.6 KB
- assets/button-variants.tsx 2.6 KB
- assets/card-variants.tsx 3.1 KB
- assets/input-variants.tsx 4.4 KB
- assets/layout-feature-grid.tsx 3.2 KB
- assets/layout-hero-section.tsx 5.6 KB
- assets/utils-cn.ts 582 B runs code
- index.js 257 B runs code
- package.json 225 B
- references/color_palettes.md 3.8 KB
- references/design_principles.md 4.3 KB
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.
- 24d ago Changed · +45 tokens per session 721decf5d8df
- 27d ago Changed · -6 lines · -79 tokens per session f873b4917350
- 1mo ago First seen · 232 lines · 79 tokens per session scan A 739026215cc3
frontend-enhancer is a skill published in the GitHub repository travisjneuman/.claude (106 stars, last pushed today), licensed MIT. It adds 45 tokens to every session and 1,475 once invoked, about $0.0002 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 2026-09-03.
Other skills, from other repositories
qa-design
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dev-frontend-design
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dev-shadcn
Integration and customization of shadcn/ui (copy-paste React components, Radix + Tailwind). Trigger when the user wants to install shadcn, add components, customize the theme, or when shadcn/ui usage is detected in the project.
design-tokens
Establish color, typography, spacing, radius and motion as named role-based tokens. Use before building any interface.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.