🎯Skills34
Manages Flow Nexus platform capabilities, enabling developers to authenticate, deploy apps, manage credits, execute sandboxes, and participate in coding challenges.
Optimizes multi-control point (MCP) configurations for enterprise AI workflows, enhancing agent coordination and performance efficiency.
Manages and optimizes memory storage, retrieval, and pattern recognition for AI agents using a structured database approach.
Identifies and analyzes performance bottlenecks in Claude Flow swarms, generating detailed reports and providing AI-powered optimization recommendations.
Enhances agent database management with advanced querying, indexing, and metadata tracking capabilities for intelligent agent deployment and coordination.
Enables distributed neural network training and deployment across E2B sandboxes with flexible architectures and scalable computational tiers.
Assists developers by providing real-time collaborative coding suggestions, code review, and contextual programming guidance alongside human programmers.
Orchestrates comprehensive software development through a systematic 5-phase methodology with multi-agent coordination and test-driven design principles.
Optimizes agent database performance by analyzing query patterns, indexing strategies, and resource allocation to enhance data retrieval and storage efficiency.
agentdb learning plugins skill from ruvnet/claude-flow
github-multi-repo skill from ruvnet/claude-flow
Coordinates multi-agent AI code reviews on GitHub PRs, performing comprehensive security, performance, and quality analysis with intelligent swarm orchestration.
Validates and ensures code quality, testing integrity, and compliance by systematically reviewing and analyzing software artifacts through automated and AI-driven verification processes.
Coordinates and manages distributed AI agents, enabling dynamic task allocation, consensus-based decision-making, and adaptive collaboration across a network of specialized agents.
Streamline GitHub project workflows with automated issue tracking, PR management, milestone planning, and team collaboration insights.
Aggregates, analyzes, and synthesizes complex reasoning patterns and knowledge fragments to enhance AI decision-making and problem-solving capabilities.
Orchestrates multi-step workflows by chaining agent outputs sequentially, enabling complex data transformations and task pipelines.
Orchestrates multi-agent coordination through queen-led swarms with specialized workers, consensus mechanisms, and collective memory.
Orchestrates advanced distributed workflows using dynamic swarm topologies, enabling parallel research, development, and testing across specialized agents.
Orchestrates cloud-based AI agent swarms with event-driven workflows, intelligent coordination, and scalable multi-topology deployment.
Orchestrates comprehensive GitHub releases with AI-powered versioning, testing, deployment, and intelligent rollback management across multiple platforms.
Stores, retrieves, and manages reasoning traces and agent knowledge across complex AI workflows, enabling persistent learning and contextual memory for intelligent systems.
Automates webhook integration and trigger management across different systems and services within the Claude-Flow platform.
Enables quantum-resistant, self-learning version control for multiple AI agents with intelligent conflict resolution and pattern recognition.
Enables deep, seamless integration of Claude's advanced capabilities across enterprise AI workflows, enhancing agent coordination and intelligent task execution.
Enhances enterprise-level security protocols for Claude-Flow by implementing comprehensive authentication, encryption, and access control mechanisms across the multi-agent AI platform.
Coordinates multiple AI agents to collaboratively solve complex problems through dynamic task allocation, consensus building, and adaptive swarm intelligence strategies.
Generates a Domain-Driven Design (DDD) architecture template with modular, scalable enterprise software design patterns and structured code organization.
Unifies and consolidates memory across different Claude agents, enabling seamless information sharing and persistent context retention during complex multi-agent workflows.
Optimizes Claude Code agent performance by dynamically analyzing and fine-tuning computational resources, response latency, and execution efficiency across multi-agent workflows.
Implements the core architectural and orchestration logic for deploying, coordinating, and managing specialized AI agents within the Claude-Flow enterprise platform.
Modernizes and enhances the command-line interface (CLI) for Claude-Flow v3, improving developer experience and interaction with the AI orchestration platform.
Benchmarks and measures performance metrics for distributed AI worker nodes in the Claude-Flow platform, evaluating computational efficiency and resource utilization.
Integrates and manages worker nodes for distributed AI task processing, enabling scalable and coordinated agent deployment across computational resources.
🔌Plugins5
Orchestrates multiple Claude AI agents into coordinated, self-learning swarms for enterprise-grade multi-agent AI development and deployment.
Orchestrates and coordinates multiple specialized AI agents using Claude Code, enabling enterprise-level multi-agent AI workflows with self-learning and consensus capabilities.
Orchestrates and coordinates multiple specialized AI agents using Claude Code, enabling enterprise-level multi-agent AI workflows with self-learning and consensus capabilities.
Orchestrates multiple Claude AI agents into coordinated, self-learning swarms for enterprise-level AI development and task execution.
Orchestrates and coordinates multiple specialized AI agents using Claude Code, enabling complex, collaborative problem-solving with enterprise-grade deployment and management capabilities.