AI 에이전트 기능을 확장하는 Claude 스킬의 전체 컬렉션을 살펴보세요.
Train and deploy distributed neural networks in isolated E2B sandboxes with automated cluster management.
Ensures codebase reliability through real-time truth scoring, automated verification checks, and high-accuracy automatic rollbacks.
Streamlines GitHub workflows through automated issue triage, swarm-coordinated task decomposition, and intelligent project board synchronization.
Facilitates collaborative AI-assisted development through automated role management, real-time code verification, and multi-mode pair programming workflows.
Orchestrates multi-agent AI swarms for parallel task execution and dynamic coordination using the agentic-flow framework.
Generates sophisticated strategic plans and autonomous growth systems using predictive insights and $100M ARR scaling methodologies.
Manages and monitors Model Context Protocol (MCP) servers across multiple AI platforms with auto-discovery and automated troubleshooting.
Analyzes and optimizes Claude Flow swarm operations by detecting performance bottlenecks and providing AI-powered recommendations.
Maintains bi-directional synchronization between implementation and documentation to eliminate documentation rot and technical debt.
Implements a structured five-phase development lifecycle with multi-agent orchestration for high-velocity, test-driven software engineering.
Automates the entire GitHub release lifecycle using AI swarms for coordinated versioning, multi-platform deployment, and intelligent changelog generation.
Automates development workflows by coordinating swarm agents, managing session states, and applying intelligent pre- and post-operation hooks.
Automates professional Blender 3D workflows, including 2D-to-3D asset transformation, procedural animation, and distributed rendering via MCP integration.
Manages the complete lifecycle of Flow Nexus resources including cloud sandboxes, app deployments, and credit systems.
Implements nine reinforcement learning algorithms to train autonomous agents that improve through experience.
Optimizes AgentDB implementations with distributed QUIC synchronization, hybrid vector search, and multi-database management patterns.
Synchronizes and manages architecture across multiple GitHub repositories using advanced AI swarm orchestration.
Performs multi-agent adversarial code reviews using specialized AI agents to ensure security, performance, and UX quality.
Coordinates multi-stage quality gates and automated validation workflows to ensure robust, production-grade software engineering.
Implements high-performance persistent memory and context management for AI agents using AgentDB and vector storage.
Enables high-performance semantic vector search and intelligent document retrieval for RAG systems and knowledge bases.
Automates complex GitHub Actions and repository management using AI swarm coordination for intelligent CI/CD orchestration.
Optimizes AgentDB vector database performance through quantization, HNSW indexing, and advanced caching strategies to reduce memory usage and accelerate search speeds.
Orchestrates complex multi-agent workflows using a hierarchical queen-led architecture and robust consensus mechanisms for collective decision-making.
Prevents technical debt and security vulnerabilities by enforcing architectural patterns and blocking anti-patterns during the coding process.
Orchestrates specialized AI agent swarms to perform comprehensive, multi-domain code reviews directly within GitHub pull requests.
Empowers developers to create professional programmatic videos using Remotion and React through expert patterns and best practices.
Enhances AI agents with high-performance adaptive learning and vector-based experience replay to improve decision-making over time.
Optimizes project task management by automating workflow activation, resolving complex dependencies, and streamlining parallel execution.
Generates comprehensive, reviewer-friendly pull request descriptions by analyzing git diffs and commit history.
Scroll for more results...