static-analysis

To run static code analysis across a polyglot codebase, configure project-config.md to define your tech stack, and the tool orchestrates language-appropriate analyzers to detect duplication, complexity, dead code, and smells automatically.

Detecting duplicate code and dead code simultaneously requires orchestrating tools like jscpd and vulture. This static analysis approach validates required analyzers and outputs structured findings for both issues in a consistent review format.

Yes, static analysis works with multiple languages like Python and JavaScript by applying project-aware scope. It runs language-appropriate tools such as ruff for Python and eslint for JavaScript based on your project configuration.

You can use semgrep for code smell detection within this static analysis workflow. The tool orchestrates semgrep alongside other analyzers to identify quality issues and outputs structured findings in JSON or Markdown formats.

Formatting static analysis findings for CI dashboard integration involves running the orchestrated analysis to produce structured outputs. The tool generates consistent JSON and Markdown reports suitable for direct review and dashboard integration.

Static analysis runs specific tools for your tech stack to apply a project-aware scope, avoiding irrelevant analyses. It reads your project-config.md to validate required analyzers and ensure only language-appropriate tools execute.