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Agent skills
anthropic-claude

Topic: anthropic-claude

1,740 skills in this topic.

AgentDB Memory Patterns Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
ruvnet/ruflo 31,446
github-workflow-automation Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
ruvnet/ruflo 31,446
github-code-review Comprehensive GitHub code review with AI-powered swarm coordination
ruvnet/ruflo 31,446
V3 Core Implementation Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing.
ruvnet/ruflo 31,446
AgentDB Advanced Features Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
ruvnet/ruflo 31,446
AgentDB Performance Optimization Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
ruvnet/ruflo 31,446
agentic-jujutsu Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
ruvnet/ruflo 31,446
agent-memory-coordinator Agent skill for memory-coordinator - invoke with $agent-memory-coordinator
ruvnet/ruflo 31,446
ReasoningBank with AgentDB Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
ruvnet/ruflo 31,446
worker-benchmarks Run comprehensive worker system benchmarks and performance analysis
ruvnet/ruflo 31,446
Verification & Quality Assurance Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
ruvnet/ruflo 31,446
agent-multi-repo-swarm Agent skill for multi-repo-swarm - invoke with $agent-multi-repo-swarm
ruvnet/ruflo 31,446
agent-safla-neural Agent skill for safla-neural - invoke with $agent-safla-neural
ruvnet/ruflo 31,446
stream-chain Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
ruvnet/ruflo 31,446
swarm-orchestration Multi-agent swarm coordination for complex tasks. Uses hierarchical topology with specialized agents to break down and execute complex work across multiple files and modules. Use when: 3+ files need changes, new feature implementation, cross-module refactoring, API changes with tests, security-related changes, performance optimization across codebase, database schema changes. Skip when: single file edits, simple bug fixes (1-2 lines), documentation updates, configuration changes, quick exploration.
ruvnet/ruflo 31,446
agent-arch-system-design Agent skill for arch-system-design - invoke with $agent-arch-system-design
ruvnet/ruflo 31,446
agent-crdt-synchronizer Agent skill for crdt-synchronizer - invoke with $agent-crdt-synchronizer
ruvnet/ruflo 31,446
flow-nexus-swarm Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
ruvnet/ruflo 31,446
AgentDB Advanced Features Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
ruvnet/ruflo 31,446
AgentDB Learning Plugins Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
ruvnet/ruflo 31,446
agent-architecture Agent skill for architecture - invoke with $agent-architecture
ruvnet/ruflo 31,446
AgentDB Memory Patterns Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
ruvnet/ruflo 31,446
agent-scout-explorer Agent skill for scout-explorer - invoke with $agent-scout-explorer
ruvnet/ruflo 31,446
memory-management AgentDB memory system with HNSW vector search. Provides 150x-12,500x faster pattern retrieval, persistent storage, and semantic search capabilities for learning and knowledge management. Use when: need to store successful patterns, searching for similar solutions, semantic lookup of past work, learning from previous tasks, sharing knowledge between agents, building knowledge base. Skip when: no learning needed, ephemeral one-off tasks, external data sources available, read-only exploration.
ruvnet/ruflo 31,446