AI 에이전트 기능을 확장하는 Claude 스킬의 전체 컬렉션을 살펴보세요.
Creates, optimizes, and debugs high-performing, production-ready prompts for Claude 4, GLM 4.7, and Gemini 3 using evidence-based techniques.
Enforces a rigorous four-phase investigation framework to identify root causes and eliminate bugs without guess-and-check thrashing.
Develops high-performance, type-safe Python 3.11+ applications with a focus on asynchronous patterns and production-ready code.
Provides a standardized framework and best practices for developing modular, context-efficient Claude Code skills.
Refines rough ideas into fully-formed software designs through structured Socratic questioning and incremental validation.
Applies Test-Driven Development principles to create robust, failure-proof Claude Code skills and process documentation.
Enforces high-quality testing standards by preventing mock-behavior testing and production code pollution.
Designs scalable, resilient microservices architectures using domain-driven design and cloud-native patterns.
Executes complex implementation plans in controlled batches with systematic review checkpoints and mandatory verification steps.
Creates isolated Git workspaces with automated environment setup and safety verification for seamless parallel branch development.
Orchestrates multiple independent Claude agents to investigate and resolve unrelated test failures and bugs concurrently.
Executes complex implementation plans by dispatching dedicated subagents for individual tasks with automated quality gates and code reviews.
Streamlines the end-of-development workflow by verifying tests and offering structured options for merging, PR creation, or cleanup.
Provides standardized architectural patterns and best practices for building robust n8n automation workflows.
Conducts comprehensive code reviews focused on quality, security, and performance using industry-standard best practices.
Designs scalable software architectures and documents system decisions using industry-standard patterns and ADRs.
Applies Test-Driven Development principles to creating, verifying, and refining documentation and skills for AI agents.
Creates distinctive, production-grade frontend interfaces with high design quality and custom aesthetic directions.
Transforms rough concepts into technical specifications through iterative questioning, trade-off analysis, and incremental validation.
Automates the creation of isolated Git worktrees with smart directory selection, dependency installation, and baseline test verification.
Eliminates flaky tests by replacing arbitrary timeouts with smart condition polling for actual state changes.
Enforces rigorous evidence-based reporting by requiring fresh command output before any task is marked as complete.
Automates CI/CD pipelines, orchestrates containerized deployments, and manages infrastructure as code for scalable, resilient production environments.
Interfaces with Grafana to query metrics, analyze logs, and manage dashboards or alerts through efficient observability workflows.
Applies a systematic, expert-level methodology to isolate and resolve complex software errors, crashes, and performance bottlenecks.
Establishes mandatory protocols for finding, announcing, and executing skills to ensure consistent AI behavior and task success.
Architects scalable, developer-friendly REST and GraphQL APIs with production-grade OpenAPI 3.1 specifications.
Architects advanced type systems and production-grade full-stack type safety to eliminate runtime errors.
Applies the TDD RED-GREEN-REFACTOR cycle to process documentation to ensure AI agents follow instructions under high-pressure scenarios.
Automates browser tasks, performs web scraping, and conducts performance analysis using Puppeteer CLI scripts.
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