Backend Architecture Review Lead
Review backend architecture for boundaries, coupling, reliability, scalability, security, operability, and maintainability.
Backend Architecture Review Lead is a free AI skill for code improvement. Review backend architecture for boundaries, coupling, reliability, scalability, security, operability, and maintainability. It works with Claude, ChatGPT, Cursor and is ready to use out of the box.
About this skill
Backend Architecture Review Lead evaluates an application's services, modules, data flow, integrations, deployment model, and operational behavior. It identifies architectural risks, unclear ownership, tight coupling, fragile dependencies, scaling bottlenecks, security weaknesses, and observability gaps, then produces prioritized recommendations.
What it does
The skill reviews diagrams, code structure, deployment descriptions, APIs, databases, queues, and runtime constraints; maps responsibilities and dependencies; distinguishes proven issues from assumptions; evaluates tradeoffs; and creates a phased architecture improvement plan with evidence, risks, effort, and acceptance criteria.
What is included
- Architecture context map
- Responsibility and boundary review
- Dependency and coupling analysis
- Reliability and scalability findings
- Security and data concerns
- Observability and operability review
- Prioritized recommendations
- Phased improvement roadmap
How to use it
1. Download the backend-architecture-review-lead-SKILL.md file 2. Upload it to your AI or engineering workspace 3. Provide architecture diagrams, module descriptions, or relevant code 4. Add known incidents, scale, latency, and delivery constraints 5. Use the review to prioritize architectural improvements
Examples
Review a Node.js backend where one API service handles authentication, billing, file processing, analytics jobs, notifications, and external integrations.
A structured architecture review covering module boundaries, shared-state risks, queue candidates, transaction boundaries, integration isolation, scaling bottlenecks, security, observability, prioritized changes, and a phased migration roadmap.
FAQ
What is this skill for?
Does it always recommend microservices?
Can it review source code?
How does it treat assumptions?
Can it evaluate scalability?
How is this different from code review?
Related Skills
Code Refactoring Planner
Analyze a codebase or module and produce a safe refactoring plan with risks, boundaries, tests, migration steps, and acceptance criteria.
Monorepo Architecture and Build Planner
Design monorepo structure, package boundaries, build graphs, ownership, caching, CI, releases, and migration strategy.
Engineering Judgment Coach
Makes an AI coding agent pause and reason like a senior engineer before writing code — right layer, reuse over rebuild, the right pattern, and honest refactor timing.