Explore MCP Servers & Agent Skills

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.

io.github.PrefectHQ/fastmcp/python-tests

Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.