Project Analyzer

To analyze a codebase for lines-of-code metrics and directory structure, use MCP analysis tools to generate a navigable tree view and calculate language distribution. You must provide a valid project path and specify file extension filters to retrieve factual project size data.

The best way to find TODO and FIXME patterns across source files is using deterministic pattern finding tools to locate technical debt. This approach searches code comments for TODOs, FIXMEs, and HACKs to prioritize maintenance work and bug fixes.

Yes, you can filter lines-of-code counts by specific file extensions like .cs and .json. The analysis requires a valid project path with extension filters to calculate blank lines, code lines, and language distribution for targeted file types.

Codebase analysis requires access to MCP analysis tools including analyze_directory, count_lines, and find_patterns. No external dependencies are needed, but you must provide a valid local project path to perform the repository overview and technical debt detection.

To triage an unfamiliar repository before onboarding, generate a project overview by analyzing the directory tree, calculating lines-of-code breakdown, and listing actionable code comments. This provides a quick understanding of project structure, size, and surface-level technical debt.

Static analysis for technical debt detection is limited to locating surface-level patterns like TODOs and FIXMEs in code comments. It does not assess runtime behavior or complex architectural issues, focusing only on textual pattern searches and deterministic lines-of-code metrics.