feature-explorer
Discovers KrakenD features, checks edition availability (CE vs EE), and provides implementation examples
Discover Content & media skills, compare source repositories and read the instructions for each workflow.
Discovers KrakenD features, checks edition availability (CE vs EE), and provides implementation examples
Creates new KrakenD configurations with best practices, proper structure, and edition-appropriate features
Detects the optimal way to run KrakenD (native binary vs Docker) and provides correct execution commands
Validates KrakenD configurations with specific error fixes, edition compatibility checks, anti-pattern detection, and Flexible Configuration support
Explains code with visual diagrams and analogies. Use when explaining how code works, teaching about a codebase, or when the user asks "how does this work?"
Comprehensive GitHub code review with AI-powered swarm coordination
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Fe...
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledg...
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building d...
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,...
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cogn...
Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges
Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill...
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 intell...
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, impleme...
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination,...
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.