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.
391 skills found
Review, audit, and build production-grade frontend interfaces with high design quality, accessibility standards, and design system compliance.
Systematic performance engineering: baseline measurement, profiling, bottleneck diagnosis, and evidence-based optimization guidance for high-performance applications.
Interactive Archon integration for knowledge base and project management. Features RAG-powered semantic search, website crawling, document versioning, and hierarchical task management via REST API.
Foundational guidelines for context engineering: optimizing token budgets, attention mechanics, and system architecture for AI agents.
UI/UX design assistant that enforces component library usage, accessibility, and design tokens for React/Next.js projects. Ensures consistent visual output using shadcn/ui, Aceternity, and other approved libraries.
Implement PCI DSS compliance for secure payment processing, cardholder data protection, and audit preparation using standardized security patterns.
Intelligent tool selector for code search. Routes queries between semantic (claudemem) and native tools (Grep/Glob) to optimize efficiency, token usage, and search accuracy.
Standardized detective skill integration for agent roles. Maps agents to code-analysis skills and enforces claudemem usage for memory-indexed code investigation.
Statistical visualization library for Python. Create publication-quality graphics like box plots, heatmaps, and violin plots with pandas integration and automatic statistical estimation.
A perspective engineering engine that researches, extracts mental models, and generates runnable persona skills based on deep expression DNA analysis.
Autonomous, parallel-safe development workflow using kanban-md. Coordinates multi-agent and human efforts with atomic claims, worktrees, and explicit handoffs.
Captures session learnings into Reusable Intelligence Infrastructure (RII). Converts one-time bug fixes and pattern discoveries into permanent agent-executable knowledge to prevent recurrence and accelerate future development.