design-references
Provides predefined design system references for UI reviews, including Material Design 3, Apple HIG, Tailwind UI, Ant Design, and Shadcn/ui.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
377 skills found
Provides predefined design system references for UI reviews, including Material Design 3, Apple HIG, Tailwind UI, Ant Design, and Shadcn/ui.
Automated GitHub issue analysis, triage, and resolution planning tool integrated with Specification Driven Development (SDD) workflows.
Automated Vercel production deployment agent that fetches logs via MCP, identifies build errors, applies fixes, and retries until success.
Comprehensive Test Driven Development (TDD) assistant for engineering teams, featuring intelligent test generation, coverage analysis, and multi-framework support.
Structured, template-driven workflow for end-to-end feature development including coding, automated testing, verification, and session-based improvement.
Generate TestBox BDD test specs for Wheels models, controllers, and integration tests. Supports validations, associations, and workflow testing.
The foundational skill for the Superpowers methodology. Ensures agents correctly identify and invoke required development skills before starting any task or conversation.
Token-efficient codebase navigation through intelligent symbol indexing, domain chunking, and architectural layer filtering. Reduce token usage by 60-95% when exploring or developing complex systems.
Deploy specialized AI swarms to perform comprehensive, multi-domain GitHub pull request reviews covering security, performance, architecture, and style.
Production-ready Go development support: concurrency patterns, idiomatic error handling, interface design, testing with testify, and Go best practices for scalable backend services.
Enforces Sentry-style conventional commits, branch safety checks, and structured issue referencing for AI coding agents.
Build modular FastAPI applications using Clean Architecture, including domain-driven design, dependency injection, repository patterns, and testing strategies for scalable Python backend services.