--- name: senior-fullstack-9ba4f1633361 description: Comprehensive fullstack development skill for building complete web applications with React, Next.js, Node.js, GraphQL, and PostgreSQL. Includes project scaffolding, code quality analysis, architecture patterns, and complete tech stack guidance. Use when building new projects, analyzing code quality, implementing design patterns, or setting up development workflows. --- # Senior Fullstack Complete toolkit for senior fullstack with modern tools and best practices. ## Quick Start ### Main Capabilities This skill provides three core capabilities through automated scripts: ```bash # Script 1: Fullstack Scaffolder python scripts/fullstack_scaffolder.py [options] # Script 2: Project Scaffolder python scripts/project_scaffolder.py [options] # Script 3: Code Quality Analyzer python scripts/code_quality_analyzer.py [options] ``` ## Core Capabilities ### 1. Fullstack Scaffolder Automated tool for fullstack scaffolder tasks. **Features:** - Automated scaffolding - Best practices built-in - Configurable templates - Quality checks **Usage:** ```bash python scripts/fullstack_scaffolder.py [options] ``` ### 2. Project Scaffolder Comprehensive analysis and optimization tool. **Features:** - Deep analysis - Performance metrics - Recommendations - Automated fixes **Usage:** ```bash python scripts/project_scaffolder.py [--verbose] ``` ### 3. Code Quality Analyzer Advanced tooling for specialized tasks. **Features:** - Expert-level automation - Custom configurations - Integration ready - Production-grade output **Usage:** ```bash python scripts/code_quality_analyzer.py [arguments] [options] ``` ## Reference Documentation ### Tech Stack Guide Comprehensive guide available in `references/tech_stack_guide.md`: - Detailed patterns and practices - Code examples - Best practices - Anti-patterns to avoid - Real-world scenarios ### Architecture Patterns Complete workflow documentation in `references/architecture_patterns.md`: - Step-by-step processes - Optimization strategies - Tool integrations - Performance tuning - Troubleshooting guide ### Development Workflows Technical reference guide in `references/development_workflows.md`: - Technology stack details - Configuration examples - Integration patterns - Security considerations - Scalability guidelines ## Tech Stack **Languages:** TypeScript, JavaScript, Python, Go, Swift, Kotlin **Frontend:** React, Next.js, React Native, Flutter **Backend:** Node.js, Express, GraphQL, REST APIs **Database:** PostgreSQL, Prisma, NeonDB, Supabase **DevOps:** Docker, Kubernetes, Terraform, GitHub Actions, CircleCI **Cloud:** AWS, GCP, Azure ## Development Workflow ### 1. Setup and Configuration ```bash # Install dependencies npm install # or pip install -r requirements.txt # Configure environment cp .env.example .env ``` ### 2. Run Quality Checks ```bash # Use the analyzer script python scripts/project_scaffolder.py . # Review recommendations # Apply fixes ``` ### 3. Implement Best Practices Follow the patterns and practices documented in: - `references/tech_stack_guide.md` - `references/architecture_patterns.md` - `references/development_workflows.md` ## Best Practices Summary ### Code Quality - Follow established patterns - Write comprehensive tests - Document decisions - Review regularly ### Performance - Measure before optimizing - Use appropriate caching - Optimize critical paths - Monitor in production ### Security - Validate all inputs - Use parameterized queries - Implement proper authentication - Keep dependencies updated ### Maintainability - Write clear code - Use consistent naming - Add helpful comments - Keep it simple ## Common Commands ```bash # Development npm run dev npm run build npm run test npm run lint # Analysis python scripts/project_scaffolder.py . python scripts/code_quality_analyzer.py --analyze # Deployment docker build -t app:latest . docker-compose up -d kubectl apply -f k8s/ ``` ## Troubleshooting ### Common Issues Check the comprehensive troubleshooting section in `references/development_workflows.md`. ### Getting Help - Review reference documentation - Check script output messages - Consult tech stack documentation - Review error logs ## Resources - Pattern Reference: `references/tech_stack_guide.md` - Workflow Guide: `references/architecture_patterns.md` - Technical Guide: `references/development_workflows.md` - Tool Scripts: `scripts/` directory --- Source attribution: SriSatyaLokesh Original project: https://github.com/SriSatyaLokesh/copilot-team-workflow License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 Gabriel Moreira Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: SriSatyaLokesh Original project: https://github.com/SriSatyaLokesh/copilot-team-workflow Attribution basis: Upstream repository explicitly recorded in package mirror path Fields of work: Development & Engineering, Product Management Roles: Data Engineer, DevOps / SRE, Full-Stack Developer, Product Manager, Technical Product Manager Specialties: Backend, DevOps, Frontend Tools: AWS, Azure, Docker, GCP, GitHub, Kubernetes, PostgreSQL Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 33c8e9c1568e247bfaf9f64e9fbf26247b4f224e2d0cb7b886a40a83068d8f87