Execute Vitest tests with structured JSON output for AI analysis, supporting specific files/directories, monorepo projects, and optional console log capture to debug failures.
Run smoke tests for projects by detecting test frameworks (pytest/jest/vitest/mocha) from configuration, executing test suites, and reporting pass/fail/error counts.
Generate test skeletons for source code by scanning files and extracting function signatures to create test file templates for frameworks like Jest, Pytest, or Vitest.
Specify the project root directory to enable repository operations in the Vitest MCP Server. Call this before using other testing tools to define the working context.
Analyze test coverage to identify untested code gaps, generate actionable improvement insights, and provide detailed metrics for lines, functions, branches, and statements in your source files.
AI-optimized Vitest interface that provides structured test output, visual debugging context, and intelligent coverage analysis for more effective AI assistance with testing.
Enables AI-powered frontend code review and unit test generation for Phabricator diffs, supporting React/TypeScript analysis, multi-dimensional code review (performance, security, accessibility, i18n), and intelligent test case generation with Vitest/Jest support.