docker-expert
Expert Docker engineer specializing in containerization, multi-stage builds, and container orchestration. Masters Docker Compose, security hardening, and production-grade container deployment strategies.
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Expert Docker engineer specializing in containerization, multi-stage builds, and container orchestration. Masters Docker Compose, security hardening, and production-grade container deployment strategies.
JavaScript and TypeScript best practices inspired by DHH's philosophy - writing elegant, maintainable, and expressive code
Analyze domain models and infer entity relationships from naming conventions. Language-agnostic. Use when understanding data models, designing database schemas, or before generating API code.
Enterprise context and session management with token budget optimization and state persistence
gRPC/Protobuf開発 - proto定義、コード生成、バックエンド実装のワークフロー
Task, ValueTask, async streams, cancellation 등 C# async/await 패턴을 사용할 때 활용합니다. 비동기 C# 코드를 작성할 때 사용합니다.
Guide for implementing Clean Architecture patterns in .NET projects. Use when creating new features, refactoring code structure, or when the user mentions "clean architecture", "layers", "domain-driven", "CQRS", or asks about project structure.
Comprehensive guide to event schema registries, schema evolution, compatibility checking, and governance for event-driven architectures
Provides guidance and templates for containerizing applications using Docker. Use when a user wants to create Dockerfiles, optimize images, set up multi-container applications with docker-compose, or follow best practices for containerization. Includes templates for frontend (Next.js), backend (FastAPI), workers, and databases.
Generate comprehensive implementation guides for coding tasks instead of writing code directly. Use when the user requests detailed implementation documentation, step-by-step development guides, or when they want to implement features themselves using tools like Cursor. Creates exhaustive guides with background context, architecture decisions, milestones with verification points, and rationale for a "build-it-yourself" workflow.
Backend API implementation patterns for scalability, security, and maintainability. Use when building APIs, services, and backend systems.
Create production-ready, agent-executable plans using verification-first approach, hierarchical decomposition, dependency mapping, and quality gates. Optional multi-AI research integration (Claude + Gemini + Codex). Use when planning complex features, migrations, refactorings, security implementations, or any multi-step agentic workflows requiring rigorous verification and parallel execution coordination.
Production-grade authentication & authorization covering JWT, cookies, sessions, hashing, MFA, OAuth2, RBAC, and permissions across all frameworks (Next.js, Express.js, FastAPI, Django, Spring, etc.). Includes intelligent pattern selection, Better Auth integration, email verification, social login, token revocation, permission management, and 10+ years security expertise. Use when implementing authentication, authorization, user management, MFA, OAuth integration, or securing APIs in any framework.
AI-powered Signal Factory Core for processing observability signals and maintaining the knowledge graph. Use when: (1) Developing Signal Engines (Freshness, Drift, Contract, DQ, Volume, Anomaly), (2) Configuring Signal Router for normalization and routing, (3) Designing Neptune graph schema for assets and lineage, (4) Implementing DynamoDB state management for incidents. Triggers: "create signal engine", "configure signal router", "design graph schema", "implement signal processing".
Autogenerate production code from disambiguated business rules (BR-*). Converts BR-* specifications into validators, constants, and logic. Use when requirements have been disambiguated into BR-*, C-*, F-* format.
Expert in modern code design standards including SOLID principles, Clean Code patterns (KISS, YAGNI, DRY, TDA), design patterns, and pragmatic software design. **ALWAYS use when designing ANY classes/modules, implementing features, fixing bugs, refactoring code, or writing functions. ** Use proactively to ensure proper design, separation of concerns, simplicity, and maintainability. Triggers - "create class", "design module", "implement feature", "refactor code", "fix bug", "is this too complex", "apply SOLID", "keep it simple", "avoid over-engineering", writing any code.
Phase 3 of feature development - Create domain events, external events, value objects, and aggregate changes for the Burraco system. Use after feature-design to implement the domain model.
EARS (Easy Approach to Requirements Syntax) format for clear requirements
Implementing formal agreements between data producers and consumers to ensure data reliability and stability.