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Found 195 Skills
Create layered architecture diagrams using HTML/CSS templates with color-coded layers and grid layouts. Best for visualizing system layers (User→Application→Data→Infrastructure), microservices architecture, and enterprise application design. NOT for pixel-perfect custom diagrams (use drawio), simple flowcharts (use mermaid), or data visualization (use vega).
Apply layered security architecture. Use when designing security controls, hardening systems, or reviewing security posture. Covers multiple security layers.
Generate Go cache implementations following GO modular architechture conventions. Use when creating cache layers in internal/modules/<module>/cache/ - user state caching, session caching, rate limiting data, temporary data storage, or any domain cache that uses Redis for fast data access with TTL support.
Generate Go repository port interfaces and implementations following GO modular architechture conventions (Gorm, PingoDB, OTEL tracing, Fx DI, ports architecture). Use when creating data access layers for entities in internal/modules/<module>/ including CRUD operations (Create, FindAll, FindByID, Update, Delete), custom queries, pagination, or transactions.
Model software around the business domain using bounded contexts, aggregates, and ubiquitous language. Use when the user mentions "domain modeling", "bounded context", "aggregate root", "ubiquitous language", or "anti-corruption layer". Covers entities vs value objects, domain events, and context mapping strategies. For architecture layers, see clean-architecture. For complexity, see software-design-philosophy.
Enforce Vertical Slice Architecture (VSA) when building applications in any language (Go, .NET/C#, Java, Kotlin, TypeScript, Python, etc.) and any type (web API, mobile backend, CLI, event-driven). Organize code by feature/use-case instead of technical layers. Each feature is a self-contained vertical slice with a single entry point that receives the router/framework handle and its dependencies. Use when the user says "vertical slice architecture", "VSA", "organizar por feature", "feature-based architecture", "slice architecture", or when building a new app or feature and the project already follows VSA conventions. Also use when reviewing or refactoring code to align with VSA principles.
This skill should be used when the user asks about Effect-TS patterns, services, layers, error handling, service composition, or writing/refactoring code that imports from 'effect'. Also covers Effect + Next.js integration with @prb/effect-next.
Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos). Use when the user wants to save, organize, sync, deduplicate, or search across their knowledge systems.
Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.
Describes how blockchain analytics platforms work in practice, typical use cases (markets, compliance, law enforcement, tax, market integrity), tool layers like visualizers and tracers, and limitations of heuristic attribution. Use when the user asks about blockchain analytics for AML, transaction monitoring, forensic tracing, institutional ops, or taint-style analysis at a high level.
Unix-composable CLI design patterns. Use when building CLI tools, designing command trees, implementing output layers, or testing CLI behavior. Covers stream separation (stdout/stderr), format flags (--json/--plain), exit codes, TTY detection, composability, and error design. Language-agnostic principles; TypeScript implementation patterns in resources/. For API design (REST, HTTP), see api-design.
Implement end-to-end Medallion Architecture (Bronze/Silver/Gold) lakehouse patterns in Microsoft Fabric using PySpark, Delta Lake, and Fabric Pipelines. Use when the user wants to: (1) design a Bronze/Silver/Gold data lakehouse, (2) set up multi-layer workspace with lakehouses for each tier, (3) build ingestion-to-analytics pipelines with data quality enforcement, (4) optimize Spark configurations per medallion layer, (5) orchestrate Bronze-to-Silver-to-Gold flows via notebooks. Triggers: "medallion architecture", "bronze silver gold", "lakehouse layers", "e2e data pipeline", "end-to-end lakehouse", "data lakehouse pattern", "multi-layer lakehouse", "build medallion", "setup medallion".