An AI code review CLI can help you inspect a change before another person sees the pull request. It is most useful when it reads a defined diff and reports concrete risks, not when it rewrites files or gives a general opinion about the repository. Keep review and implementation as separate steps so you can judge the findings on their evidence.
Choose the exact change to review
Tell the tool whether it should inspect working changes, the current branch against a base branch, or a named commit. Include the expected behavior and areas that matter, such as authorization, input validation, data handling, compatibility, or test coverage. If the change is large, split the review by feature or directory.
Some coding CLIs have a built in review command. Others can inspect a Git diff when you ask. GitHub documents a review command for its Copilot CLI; the exact syntax and behavior depend on the product you use. Check that product’s current documentation before putting a review command into a team process.
| Finding detail | What a useful review includes |
|---|---|
| Location | The changed file and line or code path |
| Reason | The condition that could cause a real defect |
| Impact | What a user, service, or data record might experience |
| Evidence | A test, code path, or reproduction that supports the concern |
Ask for a read only review first
Tell the agent not to edit files, approve the pull request, or claim that a risk is certain when the code does not establish it. Ask it to separate likely defects from questions and possible improvements. A short list of findings with exact locations is easier to act on than a broad score or a page of style preferences.
Review the code around each finding yourself. A line that looks suspicious may be protected by validation in another layer. A missing test may be intentional if the behavior is tested at a different boundary. The reviewer should help you look, not replace your understanding of the code.
A prompt to adapt
Review the change from [base branch or commit] to the current branch. Do not edit files, run commands that change external systems, or approve the pull request. Look for concrete correctness, security, data handling, and compatibility issues. For each finding, cite the changed file and relevant lines, explain a realistic impact, and say what evidence would confirm it. Separate confirmed problems from questions. If you find none, say what you reviewed and what you could not verify.Confirm the findings before asking for a fix
Reproduce a reported defect or add a test that demonstrates it. If the agent cannot explain a path from the changed code to the reported behavior, ask for clarification. Do not accept a patch simply because it addresses a review comment. A fix can introduce a second issue or change behavior outside the pull request’s purpose.
Run the required tests and inspect the final diff after a fix. Keep the review summary, the correction, and the verification result distinct. That record makes it clear which issues were real and which suggestions you chose not to use.
- Verify each reported issue against the code and product behavior.
- Reproduce it or write a test when the risk is real.
- Make and review a focused correction.
- Run the project checks and inspect the new diff.
Keep the final decision with the reviewer
Automated review can be useful before a human review, especially for a small change with explicit requirements. It can miss defects, misunderstand business rules, or report a pattern that is safe in context. A clean review result is not proof that the code is correct. Use it as another source of feedback, then follow the repository’s normal approval rules.
LucentraCode can run from a project terminal. Review its command reference and permission settings to decide how a read only review fits your own process. For more context, see the guide to reviewing AI generated code and the Git workflow guide in this category.