AI Code Review Assistant
Browser-to-TargetPaste a function or module and get a practical review focused on security risks, failure paths, and maintainability.
Stored strictly in your browser RAM/localStorage. Never touches our servers.
Security & Best-Practice Review
Audit source code for security anti-patterns (eval, leaked secrets, SQLi), legacy variable scoping, and performance issues. Connect your own LLM key for in-depth refactoring and architecture critiques.
Use it to highlight likely risks and missing checks, then confirm the real business logic and runtime behavior yourself.
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What is AI Code Review Assistant?
Frequently Asked Questions
Technical Deep Dive
Review code for risk, not just syntax
A useful code review is not a linter pass. It is a decision-making aid: it highlights risk, asks the right questions, and helps catch the mistakes that are easy to miss when a patch looks small but changes execution behavior.
The review rubric that matters
- Security: Are inputs, secrets, and trust boundaries handled correctly?
- Correctness: What happens on the failure path? Are null, timeout, and retry cases explicit?
- Performance: Is the change doing unnecessary work in tight loops or repeated render paths?
- Maintainability: Will another engineer understand the logic and failure modes in six months?
Common patterns worth flagging
Unsafe inputs
Unvalidated user input reaching SQL, shell commands, file operations, or URL redirects is a classic production issue.
Unhandled async errors
Promises that reject without clear fallbacks often turn a minor bug into an outage or partial state problem.
Expensive loops
Repeated queries or repeated work inside render or request paths can quietly break latency budgets.
Hidden side effects
Code that mutates shared state or changes external dependencies without clear boundaries is harder to trust and harder to scale.
What a strong review looks like
Good review: "This function deletes rows without checking whether the caller has permission to perform the action. The operation should be guarded by an authorization check and ideally run inside a transaction or explicit workflow."
Weak review: "This could be improved." A useful review explains the likely impact and the direction of the fix.
When to trust the result
- Use it to surface likely risk and prompt deeper questioning.
- Confirm the actual runtime path and surrounding business rules before making a change.
- Check whether the review points to a test gap or a system property that the code cannot currently prove.
A simple checklist before merge
Ask: Are inputs validated? Are secrets kept out of the browser bundle? Do we understand the failure path? Are expensive operations placed correctly? Are authorization checks enforced server-side? Are the changes readable to the next engineer? If not, the patch still needs work.