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Senior Fullstack

Fullstack development toolkit with project scaffolding for Next.js, FastAPI, MERN, and Django stacks, code quality analysis with security and complexity scor...

MIT-0 · Free to use, modify, and redistribute. No attribution required.
2 · 2k · 16 current installs · 16 all-time installs
byAlireza Rezvani@alirezarezvani
MIT-0
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Purpose & Capability
Name/description match the included assets: SKILL.md documents scaffolding and analysis workflows and the package contains two Python scripts (project_scaffolder.py and code_quality_analyzer.py) plus reference guides. Nothing in the manifest requests unrelated credentials, binaries, or services.
Instruction Scope
Runtime instructions tell the agent/user to run the included Python scripts against a given path (e.g., '.' or /path/to/project). That is expected for a scaffolder/analyzer, but both scripts read and write files under the given path. The analyzer will scan files (including .env/.env.example and config files) for secrets and security patterns — so running it against broad system paths (or root) could surface sensitive data. SKILL.md does not instruct any network exfiltration and the scripts contain no outbound network code, but exercise caution about what path you analyze and about where you store/report analyzer output.
Install Mechanism
No install spec is provided; this is instruction-only and includes local Python scripts. No downloads, package installs, or third‑party install URLs are present in the manifest.
Credentials
The skill declares no required environment variables or credentials, which is proportionate. A minor issue: the scaffolder generates example config files containing default placeholders (e.g., DATABASE_URL with 'user:pass' and SECRET_KEY 'change-me-in-production') — convenient for bootstrapping but insecure if left in production. The analyzer searches for hardcoded secrets and other sensitive strings (expected), so be aware it will surface any secrets present in scanned paths.
Persistence & Privilege
Skill is not forced-always and does not request elevated platform privileges. It does write scaffolded files into the output directory when used (expected) but does not modify other skills or system-wide configurations.
Assessment
This skill appears to do what it says: generate project boilerplate and run a local code-quality/security scan. Before using it: (1) only point the analyzer at project directories you control (avoid /, /home, or system folders) because it reads files and can surface secrets; (2) inspect generated scaffold files and .env.example values and replace default placeholders (SECRET_KEY, DB credentials) before deploying; (3) treat analyzer output as advisory — its heuristics are simplified and may produce false positives/negatives; (4) do not upload or share reports that may contain discovered secrets. If you need stronger guarantees, run the scripts in an isolated environment (container) and review the scripts' source before executing.
scripts/project_scaffolder.py:352
Environment variable access combined with network send.
Critical security concern
These patterns indicate potentially dangerous behavior. Exercise extreme caution and review the code thoroughly before installing.

Like a lobster shell, security has layers — review code before you run it.

Current versionv2.1.1
latestvk97d02y2vxd3hj12b3s2zfp7m582ky1e

License

MIT-0
Free to use, modify, and redistribute. No attribution required.

SKILL.md

Senior Fullstack

Fullstack development skill with project scaffolding and code quality analysis tools.


Table of Contents


Trigger Phrases

Use this skill when you hear:

  • "scaffold a new project"
  • "create a Next.js app"
  • "set up FastAPI with React"
  • "analyze code quality"
  • "check for security issues in codebase"
  • "what stack should I use"
  • "set up a fullstack project"
  • "generate project boilerplate"

Tools

Project Scaffolder

Generates fullstack project structures with boilerplate code.

Supported Templates:

  • nextjs - Next.js 14+ with App Router, TypeScript, Tailwind CSS
  • fastapi-react - FastAPI backend + React frontend + PostgreSQL
  • mern - MongoDB, Express, React, Node.js with TypeScript
  • django-react - Django REST Framework + React frontend

Usage:

# List available templates
python scripts/project_scaffolder.py --list-templates

# Create Next.js project
python scripts/project_scaffolder.py nextjs my-app

# Create FastAPI + React project
python scripts/project_scaffolder.py fastapi-react my-api

# Create MERN stack project
python scripts/project_scaffolder.py mern my-project

# Create Django + React project
python scripts/project_scaffolder.py django-react my-app

# Specify output directory
python scripts/project_scaffolder.py nextjs my-app --output ./projects

# JSON output
python scripts/project_scaffolder.py nextjs my-app --json

Parameters:

ParameterDescription
templateTemplate name (nextjs, fastapi-react, mern, django-react)
project_nameName for the new project directory
--output, -oOutput directory (default: current directory)
--list-templates, -lList all available templates
--jsonOutput in JSON format

Output includes:

  • Project structure with all necessary files
  • Package configurations (package.json, requirements.txt)
  • TypeScript configuration
  • Docker and docker-compose setup
  • Environment file templates
  • Next steps for running the project

Code Quality Analyzer

Analyzes fullstack codebases for quality issues.

Analysis Categories:

  • Security vulnerabilities (hardcoded secrets, injection risks)
  • Code complexity metrics (cyclomatic complexity, nesting depth)
  • Dependency health (outdated packages, known CVEs)
  • Test coverage estimation
  • Documentation quality

Usage:

# Analyze current directory
python scripts/code_quality_analyzer.py .

# Analyze specific project
python scripts/code_quality_analyzer.py /path/to/project

# Verbose output with detailed findings
python scripts/code_quality_analyzer.py . --verbose

# JSON output
python scripts/code_quality_analyzer.py . --json

# Save report to file
python scripts/code_quality_analyzer.py . --output report.json

Parameters:

ParameterDescription
project_pathPath to project directory (default: current directory)
--verbose, -vShow detailed findings
--jsonOutput in JSON format
--output, -oWrite report to file

Output includes:

  • Overall score (0-100) with letter grade
  • Security issues by severity (critical, high, medium, low)
  • High complexity files
  • Vulnerable dependencies with CVE references
  • Test coverage estimate
  • Documentation completeness
  • Prioritized recommendations

Sample Output:

============================================================
CODE QUALITY ANALYSIS REPORT
============================================================

Overall Score: 75/100 (Grade: C)
Files Analyzed: 45
Total Lines: 12,500

--- SECURITY ---
  Critical: 1
  High: 2
  Medium: 5

--- COMPLEXITY ---
  Average Complexity: 8.5
  High Complexity Files: 3

--- RECOMMENDATIONS ---
1. [P0] SECURITY
   Issue: Potential hardcoded secret detected
   Action: Remove or secure sensitive data at line 42

Workflows

Workflow 1: Start New Project

  1. Choose appropriate stack based on requirements (see Stack Decision Matrix)
  2. Scaffold project structure
  3. Verify scaffold: confirm package.json (or requirements.txt) exists
  4. Run initial quality check — address any P0 issues before proceeding
  5. Set up development environment
# 1. Scaffold project
python scripts/project_scaffolder.py nextjs my-saas-app

# 2. Verify scaffold succeeded
ls my-saas-app/package.json

# 3. Navigate and install
cd my-saas-app
npm install

# 4. Configure environment
cp .env.example .env.local

# 5. Run quality check
python ../scripts/code_quality_analyzer.py .

# 6. Start development
npm run dev

Workflow 2: Audit Existing Codebase

  1. Run code quality analysis
  2. Review security findings — fix all P0 (critical) issues immediately
  3. Re-run analyzer to confirm P0 issues are resolved
  4. Create tickets for P1/P2 issues
# 1. Full analysis
python scripts/code_quality_analyzer.py /path/to/project --verbose

# 2. Generate detailed report
python scripts/code_quality_analyzer.py /path/to/project --json --output audit.json

# 3. After fixing P0 issues, re-run to verify
python scripts/code_quality_analyzer.py /path/to/project --verbose

Workflow 3: Stack Selection

Use the tech stack guide to evaluate options:

  1. SEO Required? → Next.js with SSR
  2. API-heavy backend? → Separate FastAPI or NestJS
  3. Real-time features? → Add WebSocket layer
  4. Team expertise → Match stack to team skills

See references/tech_stack_guide.md for detailed comparison.


Reference Guides

Architecture Patterns (references/architecture_patterns.md)

  • Frontend component architecture (Atomic Design, Container/Presentational)
  • Backend patterns (Clean Architecture, Repository Pattern)
  • API design (REST conventions, GraphQL schema design)
  • Database patterns (connection pooling, transactions, read replicas)
  • Caching strategies (cache-aside, HTTP cache headers)
  • Authentication architecture (JWT + refresh tokens, sessions)

Development Workflows (references/development_workflows.md)

  • Local development setup (Docker Compose, environment config)
  • Git workflows (trunk-based, conventional commits)
  • CI/CD pipelines (GitHub Actions examples)
  • Testing strategies (unit, integration, E2E)
  • Code review process (PR templates, checklists)
  • Deployment strategies (blue-green, canary, feature flags)
  • Monitoring and observability (logging, metrics, health checks)

Tech Stack Guide (references/tech_stack_guide.md)

  • Frontend frameworks comparison (Next.js, React+Vite, Vue)
  • Backend frameworks (Express, Fastify, NestJS, FastAPI, Django)
  • Database selection (PostgreSQL, MongoDB, Redis)
  • ORMs (Prisma, Drizzle, SQLAlchemy)
  • Authentication solutions (Auth.js, Clerk, custom JWT)
  • Deployment platforms (Vercel, Railway, AWS)
  • Stack recommendations by use case (MVP, SaaS, Enterprise)

Quick Reference

Stack Decision Matrix

RequirementRecommendation
SEO-critical siteNext.js with SSR
Internal dashboardReact + Vite
API-first backendFastAPI or Fastify
Enterprise scaleNestJS + PostgreSQL
Rapid prototypeNext.js API routes
Document-heavy dataMongoDB
Complex queriesPostgreSQL

Common Issues

IssueSolution
N+1 queriesUse DataLoader or eager loading
Slow buildsCheck bundle size, lazy load
Auth complexityUse Auth.js or Clerk
Type errorsEnable strict mode in tsconfig
CORS issuesConfigure middleware properly

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