This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
日本語の概要は準備中です。原文の説明を表示しています。
Frontend development for React, Next.js, TypeScript, and Tailwind CSS. Use when building React components, optimizing Next.js performance, analyzing bundle sizes, scaffolding projects, implementing accessibility, or reviewing frontend code.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Frontend development patterns, performance optimization, and automation tools for React/Next.js applications. Scaffold projects, generate components and hooks, analyze bundle sizes, and apply React/Next.js patterns with accessibility and testing built in.
package.json + import scanning that scores bundle health and flags heavy dependencies with lighter alternatives.Before scaffolding or generating, confirm these inputs. If any is unknown or vague, ASK — do not assume:
--template; produces a different project structure)--features; decides what gets generated)frontend_scaffolder vs component_generator)Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
| Tool | Purpose | Command |
|---|---|---|
frontend_scaffolder.py | Scaffold a Next.js or React project with TypeScript + Tailwind + optional features | python scripts/frontend_scaffolder.py my-app --template nextjs --features auth,api |
component_generator.py | Generate a component/hook with optional test and Storybook story | python scripts/component_generator.py ProductCard --type client --with-test --with-story |
bundle_analyzer.py | Score bundle health and flag heavy dependencies from package.json + imports | python scripts/bundle_analyzer.py /path/to/project --verbose |
Load the reference that matches the task — keep this file lean and pull detail on demand:
What this skill covers:
package.json dependency inspection and import pattern scanningWhat this skill does NOT cover:
| Skill | Integration | Data Flow |
|---|---|---|
| senior-fullstack | Scaffolded frontend projects connect to fullstack project scaffolder for API layer setup | Frontend project structure feeds into project_scaffolder.py which adds backend, Docker, and CI/CD layers |
| senior-backend | Components consuming API data follow patterns defined by backend skill's REST/GraphQL conventions | Backend API response types imported into frontend types/ directory generated by this skill |
| senior-qa | Generated test files (--with-test) use the same Testing Library conventions that the QA skill's test strategies build upon | Component test files hand off to QA skill for integration and E2E test coverage expansion |
| senior-devops | Bundle analyzer output informs build pipeline optimization decisions | Bundle health score and dependency warnings feed into CI quality gates configured by DevOps skill |
| senior-secops | Dependency analysis identifies packages that need security audit | Heavy/outdated dependency warnings from bundle_analyzer.py trigger security review workflows |
| code-reviewer | Generated components follow patterns that the code reviewer skill validates | Code reviewer checks generated components against React/TypeScript best practices defined in this skill's references |
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
日本語の概要は準備中です。原文の説明を表示しています。
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
日本語の概要は準備中です。原文の説明を表示しています。
Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
日本語の概要は準備中です。原文の説明を表示しています。
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
日本語の概要は準備中です。原文の説明を表示しています。
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
日本語の概要は準備中です。原文の説明を表示しています。