AIエージェントの能力を拡張するClaudeスキルの完全なコレクションをご覧ください。
Develops comprehensive academic search strategies and evidence synthesis frameworks using the 5-phase VS-Research methodology.
Guides researchers through selecting and implementing optimized qualitative research designs, including phenomenology, grounded theory, and ethnography.
Identifies optimal target journals for research papers using real-time data from OpenAlex and Crossref APIs to build data-driven submission strategies.
Architects optimized quantitative research designs, experimental methodologies, and sampling strategies using an enhanced three-phase validation process.
Validates that AI-to-human text transformations preserve academic integrity, citations, and statistical accuracy.
Hardens Ruby on Rails applications by implementing industry-standard authentication, authorization, and vulnerability protections.
Analyzes your project structure and patterns to generate or update a comprehensive STANDARDS.md reference for your codebase.
Identifies and refactors common Ruby on Rails architectural flaws, performance bottlenecks, and code smells.
Guides developers through writing, debugging, and organizing comprehensive test suites for Ruby on Rails applications using RSpec or Minitest.
Analyzes product news and market shifts through strategic lenses to sharpen product intuition and strategic thinking.
Generates self-contained, high-quality documentation packages designed for AI consumption and external system integration.
Implements interactive Ruby on Rails user interfaces using Turbo and Stimulus patterns to minimize custom JavaScript.
Guides researchers through complex mixed methods study designs using systematic qualitative and quantitative integration patterns.
Optimizes Ruby on Rails applications by identifying and resolving N+1 queries, implementing efficient caching, and managing background processing.
Automates multi-database academic paper fetching and deduplication for systematic literature reviews.
Enables AI-to-AI pair programming by integrating Codex as a consultant within a tmux-managed terminal environment.
Identifies over 24 writing patterns that diminish scholarly quality and detects AI-generated linguistic markers in academic drafts.
Automates the end-to-end process of fetching, implementing, testing, and documenting software features directly from task management systems.
Models user behavior and identifies cognitive biases to improve product judgment and strategic decision-making.
Synchronizes codebase changes with technical documentation to ensure accuracy, consistency, and minimal maintenance churn.
Builds, optimizes, and executes MongoDB queries, aggregation pipelines, and complex CRUD operations.
Performs comprehensive system diagnostics and automated health checks for the Diverga plugin environment.
Safely removes unused code, exports, and dependencies through automated analysis and rigorous test-driven verification.
Enables real-time communication and coordination between multiple AI agents working in parallel.
Automates the writing, execution, and analysis of unit, integration, and end-to-end tests for modern SaaS applications.
Navigates and explores Meldoc documentation using advanced search, tree visualization, and link relationship mapping.
Provides standardized implementation patterns and guidance for testing Temporal workflows, activities, and Nexus operations using the Go SDK.
Drafts comprehensive service planning documents through an interactive Q&A process to define core concepts and features.
Implements TanStack Query v5 best practices for robust data fetching and server-state management in React applications.
Automates structured GitHub pull request reviews with incremental file analysis and AI-driven fix recommendations.
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