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## A note on code suggestions quality
- While the current AI for code is getting better and better (GPT-4), it's not flawless. Not all the suggestions will be perfect, and a user should not accept all of them automatically. Critical reading and judgment are required.
- AI models for code are getting better and better (Sonnet-3.5 and GPT-4), but they are not flawless. Not all the suggestions will be perfect, and a user should not accept all of them automatically. Critical reading and judgment are required.
- While mistakes of the AI are rare but can happen, a real benefit from the suggestions of the `improve` (and [`review`](https://pr-agent-docs.codium.ai/tools/review/)) tool is to catch, with high probability, **mistakes or bugs done by the PR author**, when they happen. So, it's a good practice to spend the needed ~30-60 seconds to review the suggestions, even if not all of them are always relevant.
- The hierarchical structure of the suggestions is designed to help the user to _quickly_ understand them, and to decide which ones are relevant and which are not:
- Only if the `Category` header is relevant, the user should move to the summarized suggestion description
- Only if the summarized suggestion description is relevant, the user should click on the collapsible, to read the full suggestion description with a code preview example.
In addition, we recommend to use the `extra_instructions` field to guide the model to suggestions that are more relevant to the specific needs of the project.
<br>
Consider also trying the [Custom Prompt Tool](./custom_prompt.md) 💎, that will **only** propose code suggestions that follow specific guidelines defined by user.
- In addition, we recommend to use the [`extra_instructions`](https://pr-agent-docs.codium.ai/tools/improve/#extra-instructions-and-best-practices) field to guide the model to suggestions that are more relevant to the specific needs of the project.
- The interactive [PR chat](https://pr-agent-docs.codium.ai/chrome-extension/) also provides an easy way to get more tailored suggestions and feedback from the AI model.