What is the level of accuracy of GitHub copilot as code quality tool according to the following parameters? a. Syntax and Correctness b. Code Quality and Best Practices c. Security d. Context Awareness e. Refactoring and Optimization f. Language-Specific Accuracy

I recognize I may not be addressing the question directly, but even if large language models (LLMs) like GitHub Copilot are not yet at the level required for complete autonomy, isn't it reasonable to anticipate that, over time, their ability to learn patterns from our codebase will evolve to a point where human intervention becomes significantly less frequent? With this in mind, I believe the focus should be on preparing for that future—gradually adopting copilots and leveraging empirical data to guide their implementation and integration into workflows.

https://github.blog/news-insights/research/does-github-copilot-improve-code-quality-heres-what-the-data-says/