common-architecture-di…
Draw architecture diagrams as editable draw.io files with a fixed house style, C4 levels, and evidence-tagged shapes. Use when producing a system context,…
Define module boundaries, dependency direction, data ownership, resilience, and distributed-system trade-offs. Use for architecture, service boundaries, coupling, scalability, or failure-cascade decisions; defer session facilitation to system-design-methodology.
$ npx -y skills add hoangnguyen0403/agent-skills-standard --skill system-design-principles --agent claude-codeHow it fires
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/system-design-principlesContext preview
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Define module boundaries, dependency direction, data ownership, resilience, and distributed-system trade-offs. Use for architecture, service boundaries, coupling, scalability, or failure-cascade decisions; defer session facilitation to system-design-methodology.
name: system-design-principles
description: "Define module boundaries, dependency direction, data ownership, resilience, and distributed-system trade-offs. Use for architecture, service boundaries, coupling, scalability, or failure-cascade decisions; defer session facilitation to system-design-methodology."
metadata:
triggers:
keywords:
- architecture
- scalability
- microservice
- microservices
- module boundary
- coupling
- bounded context
- dependency direction
- clean architecture
- cap theorem
- idempotency1. Identify bounded contexts and module boundaries 2. Name the data owner and define dependency direction (outer layers depend on inner) 3. Select communication pattern (sync REST, async event, or hybrid) and failure behavior 4. Validate CAP trade-offs only for distributed components 5. Record boundary, trade-off, and rollback in an ADR
For a failing synchronous dependency, keep the critical path explicit: timeout and circuit-break the dependency, return a defined degraded/fallback result where safe, and move non-critical notifications to an asynchronous event.
See [implementation examples](references/implementation.md) for dependency flow diagrams.
The portable SDLC standards layer for AI coding agents. Sync once, then work in your own runtime.
Repo: hoangnguyen0403/agent-skills-standard
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