Skill UI

This comprehensive tool guides developers through the entire plugin ecosystem, helping them find and recommend the optimal plugins for any given workflow or task. It covers core coordination, multi-agent collaboration, advanced memory management (Vector DB, RAG), architectural design (ADR/DDD), security auditing, and modern development methodologies. Use it when starting a new project or optimizing existing development pipelines.

A formal framework designed for evaluating AI-assisted code generation sessions. It implements Development Oriented Evals (EDD) principles, allowing users to define capability and regression criteria. The system supports multiple evaluation types—code-based, model-based, and human review—and tracks reliability using advanced metrics like pass@k, ensuring robust quality control for AI agents.

A powerful tool designed to scaffold sophisticated, custom AI agent harnesses using the metaharness CLI. It supports various templates (e.g., coding, devops, marketing) and AI hosts (e.g., Claude, Codex). Crucially, it operates with maximum safety, defaulting to a dry-run mode and refusing to write to the calling repository root, ensuring controlled and predictable development workflows.

This tool is designed to analyze source code by extracting core entities (classes, functions, modules, types) and mapping their complex relationships (imports, inheritance, calls, dependencies). It constructs a comprehensive Knowledge Graph (KG) in AgentDB. This is essential for detailed dependency analysis, understanding large codebase structures, and performing accurate impact assessments.

A comprehensive pipeline designed for Laravel projects to ensure code quality and stability before deployment. It systematically executes environment checks, linting, static analysis, full testing with coverage, security audits, migration validation, and cache preparation. Essential for robust CI/CD pipelines and pre-Pull Request validation.

A comprehensive, end-to-end playbook designed for software engineers and AI agents. It provides a structured methodology to safely introduce machine learning capabilities into existing, non-ML codebases. The process covers critical stages: problem framing, data readiness, architectural decoupling (using dedicated APIs/services), baseline model implementation, and final handoff to MLOps practices (CI/CD, monitoring).

This skill orchestrates complex, behavior-preserving code refactoring. It is designed to improve code structure—such as extracting modules, eliminating duplication, or reducing nesting—without changing the core functionality. The process follows a rigorous, multi-phase gate system, ensuring existing tests remain green throughout the entire development lifecycle, culminating in a behavior-neutral commit.

This skill is designed to assist with code quality assessment and improvement. It provides guidelines and tools for analyzing code, identifying issues, and suggesting enhancements to maintain high standards in software development projects.

A comprehensive template providing best practices for full-stack development. It covers detailed architecture design, optimal file structures for Next.js and FastAPI, standard code patterns (e.g., API responses, custom hooks), and integration guidance for modern AI services, ensuring scalable and maintainable applications.

Repo-scan is a powerful tool designed for comprehensive auditing of large and complex codebases, especially monorepos. It performs cross-stack analysis across C++, Android, iOS, and Web technologies. Key features include classifying files (core code, third-party, build artifacts), identifying known libraries, and assessing code modules into four stages: Core, Extract, Refactor, or Deprecate. Essential for planning major refactoring efforts or inheriting legacy systems.

The Safety Guard skill is designed to prevent destructive actions when working in production systems or when autonomous agents are executing tasks. It offers three protection modes (Careful, Freeze, and Guard) to monitor dangerous commands, lock specific directories, and ensure code changes are confined to intended areas, enhancing system stability and security.

A structured workflow designed to prevent 'reinventing the wheel.' Before writing custom code, this skill guides the user through analyzing needs, conducting parallel searches across multiple channels (npm, PyPI, GitHub, MCP), evaluating candidate solutions based on maintainability and community support, and making a decision (Adopt, Extend, or Custom Build). It ensures that solutions leverage existing, proven libraries and patterns.