Skill UI

This utility provides garbage collection for Claude Code configurations. It periodically scans various directories—including skills, memory files, hooks, permissions, and caches—to identify orphaned, stale, or redundant configuration items. Crucially, the process is designed to be non-destructive, always requiring explicit human confirmation for every deletion to ensure a safe, audited cleanup process.

This tool scaffolds a new Claude Code plugin from scratch, generating a standardized directory structure that meets all architectural requirements. It automatically creates necessary components, including plugin.json, skills, commands, agents, ADR documentation, and smoke tests, ensuring a robust and compliant plugin development environment.

This tool automates the creation of a standard directory structure for a Domain-Driven Design (DDD) Bounded Context. It is essential when starting a new subdomain, separating a large monolithic application, or setting up a fresh, well-organized module structure, adhering to best practices for domain, application, and infrastructure layers.

This comprehensive tool scans all project dependencies against databases of known CVEs (Common Vulnerabilities and Exposures) and security vulnerabilities. It is essential for conducting thorough security audits of third-party packages, ensuring code quality before major releases, or responding to specific security advisories. It provides actionable reports categorized by severity.

This tool analyzes Git diffs to provide comprehensive insights for Pull Requests (PRs) and large code changes. It calculates risk scores based on churn history and sensitive areas, classifies changes (e.g., feature, bugfix), recommends required reviewers, and provides detailed statistics. Use this before merging to assess code quality and minimize deployment risk.

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 comprehensive guide covering essential security best practices for Django applications. It details how to implement robust authentication, granular authorization (RBAC), and crucial security settings like CSRF/XSS protection, HSTS, and secure environment configuration to prevent common vulnerabilities in production deployments.

This tool provides comprehensive functionality for generating, updating, and maintaining project documentation. It excels at detecting 'documentation drift' by comparing the current codebase against existing documentation, flagging any inconsistencies. Users can scope generation to specific APIs or the entire project, and set up recurring maintenance schedules using cron triggers.

This guide outlines Dynamic Workflow Mode, enabling coding agents to generate structured, task-local harnesses for complex, multi-step processes. It establishes a disciplined system for temporary workarounds, extracting reusable shared skills, and implementing control pane checkpoints. Use this when tasks require custom loops, multi-agent collaboration, or reliable handoff artifacts.

Flox is a declarative, Nix-based environment manager designed to create perfectly reproducible development environments. It handles system-level dependencies (like compilers, databases, and native libraries) and ensures that complex toolchains across multiple languages (Python, Node.js, Go, etc.) function identically across macOS and Linux. Ideal for solving 'works on my machine' issues and onboarding new team members instantly.

This guide details integrating FoundationModels for running Large Language Models (LLMs) directly on the device (iOS 26). It covers advanced patterns including text generation, extracting structured data using @Generable, implementing custom tool calling for domain logic, and streaming responses for real-time UI updates. Key features emphasize strong privacy and offline capability, ensuring no data leaves the device.

A comprehensive multi-agent feedback loop inspired by Generative Adversarial Networks (GANs), designed to build complex, production-ready applications. It separates generation from evaluation, using a 'ruthlessly strict' evaluator (QA) to drive continuous iteration. This process ensures high design quality, robust functionality, and originality, overcoming the limitations of single-agent self-critique. Ideal for full-stack feature development and complex product specification implementation.