Initializing AIReady...
Technical methodology, scoring thresholds, and refactoring playbooks for AI-first engineering.
Detects logic that is repeated but written in different ways.
Analyzes how scattered related logic is across the codebase.
Measures how consistently variables, functions, and classes are named.
Measures the stability, security, and freshness of your project dependencies.
Tracks how many places need to change when a single requirement evolves.
Measures the ratio of "signal" (actual logic) to "noise" (boilerplate, dead code).
Checks for missing, outdated, or misleading documentation.
Assesses how easily an AI agent can navigate your project structure.
Quantifies how easy it is for an AI to write and run tests for your code.
Detects defensive coding patterns that indicate missing structural contracts.
Need to measure data engineering standards, pipeline quality, or security? Our Hub-and-Spoke architecture allows you to plug in your own tools.