Analyze Flask and Django projects for code quality, performance, and security.
npx skills add https://github.com/microwind/ai-skills --skill flask-django
Please help me install this Agent Skill. Skill: Flask/Django分析器 Source: https://github.com/microwind/ai-skills/tree/main/frameworks/flask-django-analyzer Command: npx skills add https://github.com/microwind/ai-skills --skill flask-django
Flask/Django 项目在结构、代码质量、安全性和性能方面常常存在缺陷。本 Skill 提供系统性的分析方法，帮助团队发现并修复潜在问题，从而提升框架层面的健壮性和可维护性。
Run the analyzer against your Flask/Django project to generate a comprehensive report.
High-intent search queries and answers about installing and using this skill.
To analyze Flask and Django projects for security and code quality, static analysis and pattern recognition are applied across Python sources, templates, and configuration files to identify architectural and security flaws.
The best way to check Django projects for CSRF and authentication vulnerabilities is through dedicated security audits that review authentication, authorization, input validation, and sensitive data protection mechanisms.
Evaluating Flask blueprint structure and application factory patterns involves structural analysis of modular designs to assess architectural compliance and identify potential maintainability improvements.
You can optimize database queries and caching strategies in Flask applications through performance analysis that evaluates model designs, query patterns, and template rendering efficiency to provide actionable recommendations.
Static analysis works effectively for Flask and Django codebases of varying sizes, performing best-practice checks across MVC/MVT architectures and application structures to ensure robustness.
A Flask and Django architecture review outputs actionable recommendations, structured improvement plans, and risk assessments derived from evaluating code quality, performance, and security flaws.
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