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Found 78 Skills
Create or update system design documents. Supports initial design and incremental design modes. Use when users need technical architecture, API design, data models, design changes, or impact analysis. Triggers on keywords like "system design", "architecture", "technical design", "API design", "design change", "impact analysis", "design change", "impact analysis".
Produces comprehensive system architecture plans for features and products including component breakdown, data flow diagrams, system boundaries, API contracts, and scaling considerations. Use for "system design", "architecture planning", "feature design", or "technical specs".
Build production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "timeout strategy", "deployment pipeline", or "chaos engineering". Covers capacity planning, health checks, and anti-fragility patterns. For data systems, see ddia-systems. For system architecture, see system-design.
Design data systems by understanding storage engines, replication, partitioning, transactions, and consistency models. Use when the user mentions "database choice", "replication lag", "partitioning strategy", "consistency vs availability", or "stream processing". Covers data models, batch/stream processing, and distributed consensus. For system design, see system-design. For resilience, see release-it.
Clarify ambiguous or conflicting requests by researching first, then asking only judgment calls. Use when prompts say "$grill-me"/"grill me", ask hard questions, request relentless interrogation, pressure-test assumptions, clarify scope/requirements, define success criteria, or request system-design/optimization decisions before implementation; stop before implementation.
Determine the best Anthropic architecture for your project by analyzing requirements and recommending the optimal combination of Skills, Agents, Prompts, and SDK primitives.
Arquitecto de soluciones digitales basadas en IA. Dos modos: (1) ANALIZAR repositorios o código existente y explicar su arquitectura para cualquier audiencia, incluyendo personas sin conocimiento técnico. (2) DISEÑAR la arquitectura completa de sistemas nuevos que usan LLMs, RAG, agentes o fine-tuning. Usa este skill cuando el usuario mencione: arquitectura de IA, diseño de sistema con LLM, capas arquitectónicas, RAG architecture, tech stack para IA, vector database, diagrama de arquitectura, componentes del sistema, embedding, retrieval, pipeline de datos, MLOps, LLMOps, evaluar enfoques, RAG vs fine-tuning, diseñar solución de inteligencia artificial, explicar repositorio, explicar código, analizar proyecto, qué hace este repo, cómo funciona este sistema, explícame este proyecto, o cualquier variación de "qué componentes necesito" o "explícame cómo funciona esto". Actívalo cuando el usuario pegue código, README, estructura de archivos, o mencione un repositorio de GitHub para analizar. También cuando quiera diseñar arquitectura nueva.
Create or evaluate an architecture decision record (ADR). Use when choosing between technologies (e.g., Kafka vs SQS), documenting a design decision with trade-offs and consequences, reviewing a system design proposal, or designing a new component from requirements and constraints.
Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design.
Comprehensive software architecture skill for designing scalable, maintainable systems using ReactJS, NextJS, NodeJS, Express, React Native, Swift, Kotlin, Flutter, Postgres, GraphQL, Go, Python. Includes architecture diagram generation, system design patterns, tech stack decision frameworks, and dependency analysis. Use when designing system architecture, making technical decisions, creating architecture diagrams, evaluating trade-offs, or defining integration patterns.
Help users design and execute platform business strategies. Use when someone is building a marketplace, creating an ecosystem, deciding on API strategy, thinking about multi-sided network effects, or building developer platforms.
This skill should be used when the user asks to "optimize prompts", "design prompt templates", "evaluate LLM outputs", "build agentic systems", "implement RAG", "create few-shot examples", "analyze token usage", or "design AI workflows". Use for prompt engineering patterns, LLM evaluation frameworks, agent architectures, and structured output design.