V3 DDD Architecture
Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.
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.
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.
Swarm 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 distributed AI systems.
swarm-advanced
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
stream-chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
sparc-methodology
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
Skill Builder
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 templates, or understand the Claude Skills specification.
ReasoningBank Intelligence
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
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.
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.
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.
github-workflow-automation
Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
github-release-management
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
github-project-management
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
github-multi-repo
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
github-code-review
Comprehensive GitHub code review with AI-powered swarm coordination
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.
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.
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.
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.
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.
deployer-workflow
Full-stack development workflow that orchestrates deployer agents (backend, frontend, database, testing, review) in a phased pipeline. Asks which backend language (Java/Go/Rust) then runs all agents.
json-formatter
Validate, format, and minify JSON files when users request JSON validation, formatting, or ask to validate their JSONs
tidbx
Provision TiDB Cloud Serverless clusters and related resources. Use when creating, deleting, or listing clusters/branches, or managing SQL users via the console.
tidbx-kysely
Set up Kysely with TiDB Cloud (TiDB X), including @tidbcloud/kysely over the TiDB Cloud serverless HTTP driver for serverless or edge environments, plus standard TCP usage. Use for Kysely + TiDB Cloud connection setup, demo snippets, and environment-specific guidance.
tidb-sql
Write, review, and adapt SQL for TiDB with correct handling of TiDB-vs-MySQL differences (VECTOR type + vector indexes/functions, full-text search, AUTO_RANDOM, optimistic/pessimistic transactions, foreign keys, views, DDL limitations, and unsupported MySQL features like procedures/triggers/events/GEOMETRY/SPATIAL). Use when generating SQL that must run on TiDB, migrating MySQL SQL to TiDB, or debugging TiDB SQL compatibility errors.
pytidb
PyTiDB (pytidb) setup and usage for TiDB from Python. Covers connecting, table modeling (TableModel), CRUD, raw SQL, transactions, vector/full-text/hybrid search, auto-embedding, custom embedding functions, and reference templates/snippets (vector/hybrid/image) plus agent-oriented examples (RAG/memory/text2sql).
tidbx-serverless-driver
Guidance for using the TiDB Cloud Serverless Driver (Beta) in Node.js, serverless, and edge environments. Use when connecting to TiDB Cloud Starter/Essential over HTTP with @tidbcloud/serverless, or when integrating with Prisma/Kysely/Drizzle serverless adapters in Vercel/Cloudflare/Netlify/Deno/Bun. Use this skill for serverless driver setup and edge runtime guidance.
tidbx-serverless-driver
Guidance for using the TiDB Cloud Serverless Driver (Beta) in Node.js, serverless, and edge environments. Use when connecting to TiDB Cloud Starter/Essential over HTTP with @tidbcloud/serverless, or when integrating with Prisma/Kysely/Drizzle serverless adapters in Vercel/Cloudflare/Netlify/Deno/Bun. Use this skill for serverless driver setup and edge runtime guidance.
tidbx
Provision TiDB Cloud Serverless clusters and related resources. Use when creating, deleting, or listing clusters/branches, or managing SQL users via the console.
tidbx-kysely
Set up Kysely with TiDB Cloud (TiDB X), including @tidbcloud/kysely over the TiDB Cloud serverless HTTP driver for serverless or edge environments, plus standard TCP usage. Use for Kysely + TiDB Cloud connection setup, demo snippets, and environment-specific guidance.
tidb-sql
Write, review, and adapt SQL for TiDB with correct handling of TiDB-vs-MySQL differences (VECTOR type + vector indexes/functions, full-text search, AUTO_RANDOM, optimistic/pessimistic transactions, foreign keys, views, DDL limitations, and unsupported MySQL features like procedures/triggers/events/GEOMETRY/SPATIAL). Use when generating SQL that must run on TiDB, migrating MySQL SQL to TiDB, or debugging TiDB SQL compatibility errors.
pytidb
PyTiDB (pytidb) setup and usage for TiDB from Python. Covers connecting, table modeling (TableModel), CRUD, raw SQL, transactions, vector/full-text/hybrid search, auto-embedding, custom embedding functions, and reference templates/snippets (vector/hybrid/image) plus agent-oriented examples (RAG/memory/text2sql).
legacy-bridge
Backward compatibility bridge that translates legacy @load patterns to new Skills format. Enables seamless migration with zero breaking changes during 6-month transition period.
skill-loader
Skill-Loader standards and best practices for Skill Loader. Includes implementation guidelines, common patterns, and testing strategies.
testing
Comprehensive testing standards including unit, integration, security, and property-based testing with TDD methodology
nist-compliance
NIST 800-53r5 control implementation, tagging, evidence collection, and compliance automation for security frameworks
security-practices
Modern security standards including Zero Trust Architecture, supply chain security, DevSecOps integration, and cloud-native protection
coding-standards
Comprehensive coding standards and best practices for maintainable, consistent software development across multiple languages and paradigms
speakturbo-tts
Give your agent the ability to speak to you real-time. Talk to your Claude! Ultra-fast TTS, text-to-speech, voice synthesis, audio output with ~90ms latency. 8 built-in voices for instant voice responses. For voice cloning, use the speak skill.
qa-use
E2E testing and browser automation with qa-use CLI. Use when the user needs to run tests, verify features, automate browser interactions, or debug test failures.
uniapp-frontend
uni-app cross-platform frontend development with Vue 3 + TypeScript. Use for: (1) Creating new uni-app projects or pages, (2) Integrating UI libraries (uView Plus, uni-ui, TuniaoUI), (3) Implementing multi-theme design systems, (4) Building WeChat Mini Programs, H5, and other platforms, (5) Setting up SCSS theming and global styles, (6) Configuring Vite build system. Includes reusable templates, component patterns, and best practices applicable to any uni-app project.
tailwind-design-system
Build scalable design systems with Tailwind CSS v4, design tokens, component libraries, and responsive patterns. Use when creating component libraries, implementing design systems, or standardizing UI patterns.
godot-gdscript-patterns
Master Godot 4 GDScript patterns including signals, scenes, state machines, and optimization. Use when building Godot games, implementing game systems, or learning GDScript best practices.
unity-ecs-patterns
Master Unity ECS (Entity Component System) with DOTS, Jobs, and Burst for high-performance game development. Use when building data-oriented games, optimizing performance, or working with large entity counts.
ios-simulator-skill
21 production-ready scripts for iOS app testing, building, and automation. Provides semantic UI navigation, build automation, accessibility testing, and simulator lifecycle management. Optimized for AI agents with minimal token output.
javascript-testing-patterns
Implement comprehensive testing strategies using Jest, Vitest, and Testing Library for unit tests, integration tests, and end-to-end testing with mocking, fixtures, and test-driven development. Use when writing JavaScript/TypeScript tests, setting up test infrastructure, or implementing TDD/BDD workflows.
modern-javascript-patterns
Master ES6+ features including async/await, destructuring, spread operators, arrow functions, promises, modules, iterators, generators, and functional programming patterns for writing clean, efficient JavaScript code. Use when refactoring legacy code, implementing modern patterns, or optimizing JavaScript applications.
nodejs-backend-patterns
Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices. Use when creating Node.js servers, REST APIs, GraphQL backends, or microservices architectures.
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