frontend-design-review
Review, audit, and build production-grade frontend interfaces with high design quality, accessibility standards, and design system compliance.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
208 skills found
Review, audit, and build production-grade frontend interfaces with high design quality, accessibility standards, and design system compliance.
Guidance and operational tips for identifying, reviewing, and managing pull requests created by the GitHub Copilot coding agent within your repository.
Enforces low Cognitive and Cyclomatic complexity in all code. Automatically maintains readability, modularity, and maintainability by preventing complex functions during development.
🛡️ GDPR & LGPD Privacy Guardian: Automated compliance scanner that detects PII exposure, insecure logging, and tracking violations in your codebase to prevent regulatory fines.
Structured task planning framework for AI agents to break down complex features, refactors, and bugs into actionable, verifiable steps.
Generate absurdly thorough, professional README.md files for any project, covering local development, system architecture, and deployment instructions.
An AI-powered skill that automatically retrieves relevant project context from your RAG knowledge base for complex coding tasks.
Convert Figma designs to project-consistent UI code using TemPad Dev MCP for precise markup, styling, and token integration.
Perform comprehensive technical analysis for stocks and ETFs using indicators like RSI, MACD, and Bollinger Bands to generate actionable trading signals and comparative reports.
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
Scaffold complex, multi-step coding tasks into actionable implementation plans and execute them autonomously using a Claude-driven bash loop.
Aggressively prune grammatical scaffolding and filler text from inputs to optimize LLM token usage while retaining core semantic content.