system-design
Design systems, services, and architectures. Trigger with "design a system for", "how should we architect", "system design for", "what's the right architecture for", or when the user needs help with API design, data modeling, or service boundaries.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install anthropics-knowledge-work-plugins-system-design
Repository
Skill path: engineering/skills/system-design
Design systems, services, and architectures. Trigger with "design a system for", "how should we architect", "system design for", "what's the right architecture for", or when the user needs help with API design, data modeling, or service boundaries.
Open repositoryBest for
Primary workflow: Analyze Data & AI.
Technical facets: Full Stack, Backend, Data / AI, Designer.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: anthropics.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install system-design into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/anthropics/knowledge-work-plugins before adding system-design to shared team environments
- Use system-design for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
--- name: system-design description: Design systems, services, and architectures. Trigger with "design a system for", "how should we architect", "system design for", "what's the right architecture for", or when the user needs help with API design, data modeling, or service boundaries. --- # System Design Help design systems and evaluate architectural decisions. ## Framework ### 1. Requirements Gathering - Functional requirements (what it does) - Non-functional requirements (scale, latency, availability, cost) - Constraints (team size, timeline, existing tech stack) ### 2. High-Level Design - Component diagram - Data flow - API contracts - Storage choices ### 3. Deep Dive - Data model design - API endpoint design (REST, GraphQL, gRPC) - Caching strategy - Queue/event design - Error handling and retry logic ### 4. Scale and Reliability - Load estimation - Horizontal vs. vertical scaling - Failover and redundancy - Monitoring and alerting ### 5. Trade-off Analysis - Every decision has trade-offs. Make them explicit. - Consider: complexity, cost, team familiarity, time to market, maintainability ## Output Produce clear, structured design documents with diagrams (ASCII or described), explicit assumptions, and trade-off analysis. Always identify what you'd revisit as the system grows.