code-review

Code review automation classifies your git changes by file type and applies domain-specific review criteria to each. It detects frontend versus backend modifications, references the appropriate review guide, and generates structured feedback with severity levels and code examples ready for integration.

Yes. Automated code review evaluates quality, security, tests, typing safety, and performance against staged and unstaged git changes. It applies both frontend and backend best practices, flagging issues with concrete examples and severity ratings for consistent enforcement across your codebase.

Perspective-based review separates frontend and backend concerns by automatically detecting file types and directories, then applying distinct review guidance to each. This eliminates context switching and ensures domain-specific quality checks reach the right reviewers without manual categorization.

The skill generates structured, report-ready feedback including file-level summaries, issue severities, code examples, and best practices formatted for RAG system ingestion. This enables semantic retrieval and contextual integration into downstream analysis or knowledge systems.

No. Automated code review detects frontend and backend file types by extension and directory structure, eliminating manual classification. It applies the appropriate review guidance automatically based on what changed.

Beyond issue detection, it delivers file-level summaries, severity classifications, concrete code examples, and domain-specific best practices. Output is structured for report generation and systems integration, reducing review time while maintaining consistency.