ludo-technologies

Analyze Python module architecture using pyscn - class coupling (CBO), cohesion (LCOM), dependency cycles, and module communities. Use when user asks about architecture, module structure, coupling, circular dependencies, or which files to review or change…

Run the pyscn command-line tool for Python code quality analysis - CI/CD quality gates, HTML/JSON/CSV reports, full analysis runs, and project configuration. Use when user wants a CI check, a shareable report file, or to configure pyscn for a project.

Get an overall Python code quality health score using pyscn. Use when user asks how healthy or good the code is, wants a quality overview, a grade, a summary of technical debt, or a before/after quality comparison.

Find refactoring targets in Python code using pyscn - duplicate code (clones), overly complex functions, and dead code. Use when user asks about refactoring, code duplication, complexity hotspots, unreachable code, or cleaning up a codebase.

Analyze JavaScript/TypeScript module architecture using jscan - class coupling (CBO), instability metrics, and circular dependency detection. Use when user asks about architecture, module structure, coupling, or circular dependencies.

Run the jscan command-line tool for JavaScript/TypeScript code quality analysis - CI/CD quality gates, HTML/JSON reports, full analysis runs, and project configuration. Use when user wants a CI check, a shareable report file, or to configure jscan for a…

Get an overall JavaScript/TypeScript code quality health score using jscan. Use when user asks how healthy or good the code is, wants a quality overview, a grade, a summary of technical debt, or a before/after quality comparison.

Find refactoring targets in JavaScript/TypeScript code using jscan - duplicate code (clones), overly complex functions, and dead code. Use when user asks about refactoring, code duplication, complexity hotspots, unreachable code, or cleaning up a codebase.

Python coding standards and best practices covering error handling, performance optimization, async patterns, SOLID design principles, documentation, data validation, and object-oriented programming. Use when writing, reviewing, or refactoring Python code, or…

Python development tooling configuration and best practices for ruff, mypy, pytest, pyscn, and uv. Use when setting up a Python project, configuring linters, formatters, type checkers, or test frameworks, or when editing pyproject.toml or tool config files.

Python test-writing best practices covering test structure, fixtures, parametrization, and mocking with pytest. Use when writing, reviewing, or refactoring tests, adding test coverage, or working in tests directories and conftest.py.