Explore MCP Servers & Agent Skills

io.github.xenitV1/Antigravity-Workflows/nextjs-best-practices

Next.js App Router principles. Server Components, data fetching, routing patterns.

io.github.agentscope-ai/agentscope-java/writing-skill

A skill for writing and content creation

io.github.harperreed/dotfiles/swiftui-view-refactor

Refactor and review SwiftUI view files for consistent structure, dependency injection, and Observation usage. Use when asked to clean up a SwiftUI view’s layout/ordering, handle view models safely (non-optional when possible), or standardize how dependencies and @Observable state are initialized and passed.

io.github.ruvnet/RuView/verification-quality

Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

io.github.ruvnet/RuView/v3-cli-modernization

CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intelligent workflow automation.

io.github.ruvnet/RuView/v3-memory-unification

Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).

io.github.ruvnet/RuView/hooks-automation

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, and neural pattern training for enhanced development workflows.

io.github.ruvnet/RuView/reasoningbank-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.

io.github.ruvnet/RuView/pair-programming

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. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.

io.github.ruvnet/RuView/v3-swarm-coordination

15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.

io.github.ruvnet/RuView/v3-security-overhaul

Complete security architecture overhaul for claude-flow v3. Addresses critical CVEs (CVE-1, CVE-2, CVE-3) and implements secure-by-default patterns. Use for security-first v3 implementation.

io.github.ruvnet/RuView/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.

io.github.ruvnet/RuView/github-workflow-automation

Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management

io.github.ruvnet/RuView/github-release-management

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

io.github.ruvnet/RuView/github-project-management

Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning

io.github.ruvnet/RuView/github-multi-repo

Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration

io.github.ruvnet/RuView/github-code-review

Comprehensive GitHub code review with AI-powered swarm coordination

io.github.ruvnet/RuView/v3-mcp-optimization

MCP server optimization and transport layer enhancement for claude-flow v3. Implements connection pooling, load balancing, tool registry optimization, and performance monitoring for sub-100ms response times.

io.github.ruvnet/RuView/agentdb-vector-search

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 knowledge bases.

io.github.ruvnet/RuView/agentdb-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.

io.github.ruvnet/RuView/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.

io.github.ruvnet/RuView/agentdb-learning

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.

io.github.ruvnet/RuView/agentdb-advanced

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.

io.github.sugarforever/01coder-agent-skills/nextjs-security-scan

Comprehensive security vulnerability scanner for Next.js and TypeScript/JavaScript projects. Detects OWASP Top 10 vulnerabilities, XSS, injection flaws, authentication issues, hardcoded secrets, and Next.js-specific security problems. Audits dependencies for known CVEs and generates actionable security reports.