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Found 102 Skills
Use when planning system architecture to ensure nothing is missed. Provides structured questions covering scalability, security, data, and operational dimensions before implementation.
Agent skill for arch-system-design - invoke with $agent-arch-system-design
Use this skill when designing distributed systems, architecting scalable services, preparing for system design interviews, or making infrastructure decisions. Triggers on load balancing, CAP theorem, sharding, replication, caching strategies, message queues, microservices architecture, database selection, rate limiting, and any task requiring high-level system architecture decisions.
Coaches end-to-end ML system design interviews covering inference pipelines, recommendation systems, RAG, feature stores, and monitoring. Use for L6+ design rounds, ML architecture whiteboarding, system design practice, serving tradeoff analysis. Activate on "ML system design", "ML interview", "recommendation system design", "RAG architecture", "feature store design", "model serving". NOT for coding interviews, behavioral questions, ML theory quizzes, or paper implementations.
Design data systems by understanding storage engines, replication, partitioning, transactions, and consistency models. Use when the user mentions "database choice", "replication lag", "partitioning strategy", "consistency vs availability", or "stream processing". Covers data models, batch/stream processing, and distributed consensus. For system design, see system-design. For resilience, see release-it.
Build production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "timeout strategy", "deployment pipeline", or "chaos engineering". Covers capacity planning, health checks, and anti-fragility patterns. For data systems, see ddia-systems. For system architecture, see system-design.
Clarify ambiguous or conflicting requests by researching first, then asking only judgment calls. Use when prompts say "$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.
Expert-level system design, architecture patterns, scalability, and distributed systems
Transform PRD (Product Requirements Document) into actionable engineering specifications. Creates detailed technical specs that developers can implement step-by-step without ambiguity. Covers data modeling, API design, business logic, security architecture, deployment, and agent system design. Use when: converting product requirements to technical specs, validating PRD completeness, planning technical implementation, creating task breakdowns, or defining test specifications. Triggers: 'PRD to spec', 'convert requirements', 'technical spec from PRD', 'engineering doc from requirements', 'validate PRD'.
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.
Agent skill for specification - invoke with $agent-specification
Principal backend engineering intelligence for Node.js runtime systems. Actions: plan, design, build, implement, review, fix, optimize, refactor, debug, secure, scale backend code and architectures. Focus: correctness, reliability, performance, security, observability, scalability, operability, cost.