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# Improve Tool
The `improve` tool scans the PR code changes, and automatically generate committable suggestions for improving the PR code.
The `improve` tool scans the PR code changes, and automatically generates committable suggestions for improving the PR code.
It can be invoked manually by commenting on any PR:
```
/improve
@ -17,7 +17,7 @@ An extended mode, which does not involve PR Compression and provides more compre
/improve --extended
```
Note that the extended mode divides the PR code changes into chunks, up to the token limits, where each chunk is handled separately (multiple calls to GPT-4).
Hence, the total number of suggestions is proportional to the number of chunks, i.e. the size of the PR.
Hence, the total number of suggestions is proportional to the number of chunks, i.e., the size of the PR.
### Configuration options
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- `final_clip_factor`: factor to remove suggestions with low confidence. Default is 0.9.
#### summarize mode
- `summarize`: if set to true, the tool will summarize the PR code changes. Default is false.
- `summarize`: if set to true, the tool will present the code suggestions in a compact way. Default is false.
In this mode, instead of presenting commitable suggestions, the different suggestions will be combined into a single compact comment, with a significant smaller PR footprint.
In this mode, instead of presenting committable suggestions, the different suggestions will be combined into a single compact comment, with significantly smaller PR footprint.
For example:
@ -46,7 +46,7 @@ For example:
#### A note on code suggestions quality
- With current level of AI for code (GPT-4), mistakes can happen. Not all the suggestions will be perfect, and a user should not accept all of them automatically.
- With the current level of AI for code (GPT-4), mistakes can happen. Not all the suggestions will be perfect, and a user should not accept all of them automatically.
- Suggestions are not meant to be [simplistic](./../pr_agent/settings/pr_code_suggestions_prompts.toml#L34). Instead, they aim to give deep feedback and raise questions, ideas and thoughts to the user, who can then use his judgment, experience, and understanding of the code base.