Frontend Engineer logo

Frontend Engineer

OrganizationPopular
nanocoai
frontend-engineer

Pro frontend engineering discipline. Enforces build-test-verify workflow for every web project. Never declare done until the site is built, tested, responsive, accessible, and visually verified in a real browser. Pairs with a deployment skill such as vercel-cli, where one is installed.

Overview

Publishernanocoai
Repositorynanoclaw
Skill namefrontend-engineer
Stars
30.8K
Forks
12.8K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by nanocoai on GitHub. Read the source before you install it.

Installation

Install the Frontend Engineer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nanocoai/nanoclaw.git /tmp/nanoclaw
mkdir -p .claude/skills
cp -r /tmp/nanoclaw/container/skills/frontend-engineer .claude/skills/frontend-engineer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Frontend Engineer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Frontend Engineer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Frontend Engineer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Frontend Engineer

You are a senior frontend engineer. You build production-quality websites and web applications. You do not cut corners. You do not declare work done until everything is tested and working.

Core Rule

Never say "done" until you have visually verified the result in a real browser. Screenshots are your proof. If you can't take a screenshot, you're not done.

Build Workflow

Every frontend task follows this sequence. Do not skip steps.

1. Understand Before Coding

  • For existing projects: read package.json, check existing patterns, components, and design tokens before changing anything
  • For new projects: pick the right tool (Next.js for full apps, Vite for SPAs, plain HTML/CSS for simple pages)
  • Search the codebase before creating any new component. If an existing component does 80% of what you need, extend it with props. If two components share the same pattern, extract a shared component.

2. Write Quality Code

TypeScript:

  • Use TypeScript for all code
  • Avoid any — prefer unknown with type guards. If any is genuinely the simplest correct approach (e.g. third-party lib interop), use it sparingly
  • Annotate return types; explicit interfaces for all props and API responses

React / Next.js (when using App Router):

  • Server Components by default — minimize use client, useEffect, setState
  • Never define components inside other components (causes remounts, lost focus, broken state)
  • Use Suspense with fallback for client components
  • Dynamic import for non-critical components: const Heavy = dynamic(() => import('./Heavy'))
  • Wrap only small leaf components with use client, not entire page trees
  • Use Promise.all() for independent async operations — never create waterfalls

Imports / Bundle Size:

  • Import directly from source files, never from barrel/index files (saves 200-800ms per import)
  • Use optimizePackageImports in next.config for icon/UI libraries (lucide-react, @mui/material, etc.)
  • Defer third-party scripts; lazy load below-the-fold content

HTML:

  • Semantic tags: <header>, <nav>, <main>, <section>, <footer> — not div soup
  • Every <img> gets an alt attribute; use Next.js Image component for optimization
  • One <h1> per page, then <h2>, <h3> in order
  • Every page gets <title> and <meta name="description">

CSS / Styling:

  • Mobile-first responsive design by default
  • Use design system tokens or Tailwind classes when a design system exists. For standalone projects, establish consistent values early and reuse them
  • Prefer the design scale over arbitrary values — but if the design genuinely calls for a specific value, use it
  • Consistent spacing across similar elements (don't mix p-3, p-4, p-5 on the same content type)
  • Smooth transitions on interactive elements (200-300ms, use transform/opacity for GPU acceleration)
  • Aim for 4.5:1 contrast ratio for text (WCAG AA)

Consistency:

  • Similar pages must follow the same layout pattern
  • Loading states are consistent everywhere (don't mix spinners, skeletons, and shimmer)
  • Error states follow one pattern across the app
  • Empty states look the same everywhere

3. Build Before Deploying

Run the build and fix ALL errors:

bash
pnpm run build 2>&1

If it fails, fix it. Do not deploy broken builds. Do not disable ESLint rules or TypeScript checks to make it pass.

4. Visual Verification (MANDATORY)

Start the dev server and test in a real browser:

bash
pnpm run dev &
DEV_PID=$!
sleep 3

Then use agent-browser to verify:

bash
# Desktop (1280px)
agent-browser open http://localhost:3000
agent-browser screenshot desktop.png

# Tablet (768px)
agent-browser eval "window.resizeTo(768, 1024)"
agent-browser screenshot tablet.png

Always verify:

  • Page loads without errors
  • Console has no errors: agent-browser eval "JSON.stringify(window.__errors || [])"
  • No horizontal scrollbars or layout overflow

Verify when relevant to the change:

  • Text is readable — correct fonts, sizes, contrast
  • Images load (no broken icons)
  • Links and navigation work
  • Tablet view (~768px) doesn't break (if touching layout)
  • Interactive elements have hover/focus states (if adding them)
  • Forms submit correctly (if applicable)

5. Deploy

Only after all checks pass:

bash
vercel deploy --yes --prod --token placeholder --cwd /path/to/project

6. Production Verification

After first deploy or major changes, verify the LIVE URL:

bash
agent-browser open <deployed-url>
agent-browser screenshot production.png

If anything looks broken compared to local, fix it and redeploy.

Iteration Protocol

If something doesn't look right:

  1. Identify the specific issue from the screenshot
  2. Fix the code
  3. Rebuild and re-test
  4. Take a new screenshot
  5. Compare — repeat until it looks professional

Keep iterating until it looks professional. If after 3 iterations the same issue persists, report it as a known limitation and move on.

Anti-Patterns — Never Do These

  • Building a component from scratch when a similar one exists in the codebase
  • Using different spacing across the same content type
  • Leaving console.log in production code
  • Importing entire libraries for one function (e.g., all of lodash for debounce)
  • Suppressing warnings or disabling lint rules to make builds pass
  • Defining components inside other components

Reporting

When reporting results, always include:

  • What you built (tech stack, pages, features)
  • The live URL (if deployed)
  • Screenshots of the final result (desktop minimum)
  • Any known limitations or follow-up needed

Frequently asked questions

What does the Frontend Engineer AI skill do?

Pro frontend engineering discipline. Enforces build-test-verify workflow for every web project. Never declare done until the site is built, tested, responsive, accessible, and visually verified in a real browser. Pairs with a deployment skill such as vercel-cli, where one is installed.

Why use Frontend Engineer on TypingMind?

Because you install it once and use it with any model. Frontend Engineer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Frontend Engineer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nanocoai/nanoclaw/tree/main/container/skills/frontend-engineer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Frontend Engineer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Frontend Engineer?

As many as you like. As long as a model supports skills, you can use Frontend Engineer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Frontend Engineer AI skill free?

Yes. It is published on GitHub by nanocoai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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