Explore our collection of Agent Skills to enhance your AI workflow.
Orchestrates a multi-agent debate between independent AI judges to reach a high-accuracy consensus on solution quality.
Configures a Docker-based MCP server for searching and downloading academic papers from arXiv, PubMed, and other scholarly sources.
Executes complex reasoning tasks through systematic multi-agent exploration, pruning, and solution synthesis.
Automates the installation and configuration of Codemap CLI to provide AI agents with intelligent codebase visualization and lifecycle hooks.
Configures standardized code formatting rules and style guidelines within CLAUDE.md to ensure consistent AI-generated code.
Guides the creation of high-quality Model Context Protocol (MCP) servers for seamless LLM integration with external services.
Orchestrates complex coding tasks by decomposing them into verified sequential sub-steps using specialized AI agents and model selection.
Automates complex task implementation using an orchestrator-agent pattern with integrated LLM-as-Judge quality verification.
Applies classic 'The Elements of Style' principles to documentation to ensure clarity, brevity, and professional polish.
Orchestrates specialized sub-agents with intelligent model selection and mandatory self-critique for high-quality task execution.
Optimizes software development workflows and code quality using intelligent Kaizen analysis techniques like Gemba Walks and Value Stream Mapping.
Maintains and synchronizes project documentation, READMEs, and API references with local code changes using a multi-agent workflow.
Curates and persists project-specific insights and patterns into CLAUDE.md to improve long-term agent performance.
Streamlines parallel development by automating Git worktree creation and environment setup with automatic dependency installation.
Streamlines merging changes from multiple git worktrees using selective checkouts, interactive patching, and guided cherry-picking strategies.
Transforms GitHub issues into comprehensive technical specifications and implementation plans automatically.
Automates the configuration of Context7 MCP to provide AI agents with up-to-date technology documentation and code examples.
Automates the creation of standardized, emoji-enhanced conventional commit messages while managing branch workflows and code quality.
Exports open GitHub issues into local markdown files to provide structured project context for AI development.
Conducts iterative Five Whys root cause analysis to uncover systemic issues and propose fundamental solutions.
Transforms draft task specifications into implementation-ready plans through multi-agent analysis and quality-gated verification.
Evaluates and scores AI-generated work using a specialized, context-isolated sub-agent to ensure high-quality results.
Generates structured, high-quality Claude Code commands using standardized patterns and MCP tool integrations.
Automates the creation of structured task files and project directory hierarchies for streamlined workflow management.
Implements a robust Domain-Driven Design and clean architecture foundation for modular TypeScript agent systems.
Implements accessibility-first React Native user interfaces with platform-specific design systems and touch-optimized patterns.
Implements professional backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design for scalable systems.
Transforms complex business data into actionable insights through advanced analytics, predictive modeling, and strategic KPI frameworks.
Bootstraps production-ready FastAPI backends integrated with Supabase Auth and SQLModel database abstraction.
Diagnoses and resolves configuration issues for Claude Code plugins and skills to ensure they activate and function correctly.
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