Loading...
Loading...
Found 70 Skills
Principal backend engineering intelligence for Python services and data 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.
Principal backend engineering intelligence for TypeScript services. 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.
Principal backend engineering intelligence for JavaScript services. 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.
Apply cloud-native architecture patterns. Use when designing for scalability, resilience, or cloud deployment. Covers microservices, containers, and distributed systems.
Technical implementation planning and architecture design. Capabilities: feature planning, system architecture, technical evaluation, implementation roadmaps, requirement breakdown, trade-off analysis, codebase analysis, solution design. Actions: plan, architect, design, evaluate, breakdown technical solutions. Keywords: implementation plan, technical design, architecture, system design, roadmap, requirements analysis, trade-offs, technical evaluation, feature planning, solution design, scalability, security, maintainability, sprint planning, task breakdown. Use when: planning new features, designing system architecture, evaluating technical approaches, creating implementation roadmaps, breaking down complex requirements, assessing technical trade-offs.
Build FastAPI applications using Clean Architecture principles with proper layer separation (Domain, Infrastructure, API), dependency injection, repository pattern, and comprehensive testing. Use this skill when designing or implementing Python backend services that require maintainability, testability, and scalability.
Master plugin folder structure, manifest design, and architectural patterns. Learn to organize plugins for scalability and maintainability.
Technical architect assistant that helps design robust, scalable, and maintainable backend/frontend architectures. Provides visual diagrams, pattern recommendations, API design guidance, and stack selection advice. Use when designing system architecture, choosing tech stacks, planning scalability, designing APIs, or creating architectural documentation. Covers microservices, monoliths, serverless, event-driven patterns, and modern frameworks like Next.js and Supabase.
Deep Python code review of changed files using git diff analysis. Focuses on production quality, security vulnerabilities, performance bottlenecks, architectural issues, and subtle bugs in code changes. Analyzes correctness, efficiency, scalability, and production readiness of modifications. Use for pull request reviews, commit reviews, security audits of changes, and pre-deployment validation. Supports Django, Flask, FastAPI, pandas, and ML frameworks.
Use when evaluating business model viability, analyzing profitability per customer/product/transaction, validating startup metrics (CAC, LTV, payback period), making pricing decisions, assessing scalability, comparing business models, or when user mentions unit economics, CAC/LTV ratio, contribution margin, customer profitability, break-even analysis, or needs to determine if a business can be profitable at scale.
Execute comprehensive load and stress testing to validate API performance and scalability. Use when validating API performance under load. Trigger with phrases like "load test the API", "stress test API", or "benchmark API performance".
Test application performance, scalability, and resilience. Use when planning load testing, stress testing, or optimizing system performance.