Découvrez les skills databases architecture patterns, comparez leurs dépôts et consultez leurs instructions.
Use this agent when you need to analyze code changes from an architectural perspective, evaluate system design decisions, or ensure that modifications align with established architectural patterns. This include...
Use this agent when you need to review database migrations, data models, or any code that manipulates persistent data. This includes checking migration safety, validating data constraints, ensuring transaction...
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes a...
Spot patterns appearing in 3+ domains to find universal principles
Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions.
Search app data flow - query flow diagram (user input → debounce → alias check → provider dispatch → aggregate → rank → UI), state management patterns (mutableStateOf, mutableStateListOf, StateFlow, SharedFlow)...
Systematic debugging skill for complex issues. Use when encountering bugs, test failures, or unexpected behavior. Enforces explore-plan-debug-fix workflow to prevent premature fixes.
Troubleshoot agent & tool failures in scheduling orchestration. Use when MCP tools fail, agent communication breaks, constraint engines error, or database operations timeout. Provides systematic incident respon...
Invoke ARCHITECT Deputy for systems architecture, design decisions, and technical infrastructure work.
Delta Live Tables (DLT) pipeline patterns and examples for building declarative, self-healing data pipelines with automatic quality enforcement and lineage tracking.
Modern deployment with Databricks Asset Bundles (DAB), supporting multi-environment configurations and CI/CD integration.
Bronze/Silver/Gold layer design patterns and templates for building scalable data lakehouse architectures. Includes incremental processing, data quality checks, and optimization strategies.
Unity Catalog governance patterns, permissions models, security best practices, and policy enforcement for enterprise data governance.
RBAC/ABAC implementation patterns, least privilege access, row-level security, column masking, and access review workflows.
Data product design patterns with contracts, SLAs, and governance for building self-serve data platforms using Data Mesh principles.
Delta Sharing configuration, monitoring, and recipient management for secure cross-organization data sharing.
GitHub Actions and CI/CD patterns for Databricks, including automated testing, deployment, and quality gates.
Design API contracts, data models, and UI/UX specifications. Use for API design, data modeling, UI wireframes, and design systems.
Design system and security architecture. Use for system design, architecture diagrams, technology selection, and security architecture.
Domain-Driven Design system for software development. Use when designing new systems with DDD principles, refactoring existing codebases toward DDD, generating code scaffolding (entities, aggregates, repositori...
Provides workflow guidelines for problem-solving, git commits, GitHub issues, PRs, build management, and testing. Use when planning tasks, creating issues, submitting PRs, managing builds, or writing tests.
Provides API design guidelines for REST, GraphQL, versioning, logging, observability, and architecture patterns. Use when designing APIs, reviewing architecture, implementing microservices, or setting up monito...
Provides workflow guidelines for problem-solving, git commits, GitHub issues, PRs, build management, and testing. Use when planning tasks, creating issues, submitting PRs, managing builds, or writing tests.
Provides API design guidelines for REST, GraphQL, versioning, logging, observability, and architecture patterns. Use when designing APIs, reviewing architecture, implementing microservices, or setting up monito...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.