reducing-complexity
Managing complexity is software's primary technical imperative - all other goals are secondary
Managing complexity is software's primary technical imperative - all other goals are secondary
Design in pseudocode first, iterate approaches, then translate to code
Specialized skill for Rails business logic with ActiveInteraction, AASM state machines, and ActiveDecorator. Use when implementing complex operations, state transitions, or presentation logic. Enforces interaction pattern over service objects.
Guide for building, auditing, and refactoring Swift code using modern concurrency patterns (Swift 6+). This skill should be used when working with async/await, Tasks, actors, MainActor, Sendable types, isolation domains, or when migrating legacy callback/Combine code to structured concurrency. Covers Approachable Concurrency settings, isolated parameters, and common pitfalls.
brainbaseのアーキテクチャパターン(EventBus、Reactive Store、DI Container、Service Layer)への準拠をチェックし、違反箇所を修正提案する4 Phase Orchestrator Skill。
Multi-agent coordination and synthesis patterns. Use when orchestrating multiple specialized agents, implementing fan-out/fan-in workflows, or synthesizing outputs from parallel agents.
Distributed locking patterns with Redis and PostgreSQL for coordination across instances. Use when implementing exclusive access, preventing race conditions, or coordinating distributed resources.
Database version control and change management patterns. Use when managing schema history, coordinating database changes across environments, implementing audit trails, or versioning database objects.
SOLID principles, hexagonal architecture, ports and adapters, and DDD tactical patterns for maintainable backends. Use when implementing clean architecture, decoupling services, separating domain logic, or creating testable architecture.
Message queue patterns with RabbitMQ, Redis Streams, and Kafka. Use when implementing async communication, pub/sub systems, event-driven microservices, or reliable message delivery.
CQRS (Command Query Responsibility Segregation) patterns for separating read and write models. Use when optimizing read-heavy systems, implementing event sourcing, or building systems with different read/write scaling requirements.
Python asyncio patterns with TaskGroup, structured concurrency, and modern 3.11+ features. Use when implementing concurrent operations, async context managers, or high-performance async services.
Idempotency patterns for APIs and event handlers. Use when implementing exactly-once semantics, deduplicating requests, or building reliable distributed systems.
LangGraph conditional routing patterns. Use when implementing dynamic routing based on state, creating branching workflows, or building retry loops with conditional edges.
Expert guidance on Swift Concurrency concepts. Use when working with async/await, Tasks, actors, MainActor, Sendable, isolation domains, or debugging concurrency compiler errors. Helps write safe concurrent Swift code.
Transactional outbox pattern for reliable event publishing. Use when implementing atomic writes with event delivery, ensuring exactly-once semantics, or building event-driven microservices.
Saga patterns for distributed transactions with orchestration and choreography approaches. Use when implementing multi-service transactions, handling partial failures, or building systems requiring eventual consistency with compensation.
gRPC with Python using grpcio and protobuf for high-performance microservice communication. Use when implementing service-to-service APIs, streaming data, or building polyglot microservices requiring strong typing.
Domain-Driven Design tactical patterns for complex business domains. Use when modeling entities, value objects, domain services, repositories, or establishing bounded contexts.
Event sourcing patterns for storing state as a sequence of events. Use when implementing event-driven architectures, CQRS, audit trails, or building systems requiring full history reconstruction.
Use when planning system architecture to ensure nothing is missed. Provides structured questions covering scalability, security, data, and operational dimensions before implementation.
Advanced Celery patterns including canvas workflows, priority queues, rate limiting, multi-queue routing, and production monitoring. Use when implementing complex task orchestration, task prioritization, or enterprise-grade background processing.
LangGraph state management patterns. Use when designing workflow state schemas, using TypedDict vs Pydantic, implementing accumulating state with Annotated operators, or managing shared state across nodes.