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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →To stop a coding agent from flagging harmless style differences, give it a clear threshold for what counts as a finding: report only specific, actionable issues introduced by the change that materially affect correctness, security, performance, or maintainability. Explicitly exclude non-blocking style and formatting preferences, while allowing exceptions when they obscure meaning or violate a documented project standard.
Define what deserves a review comment
“Be less picky” is too vague to guide a review. State which issues qualify, what evidence a comment needs, and which low-impact issues to leave out. A useful finding points to a discrete problem, explains when it occurs, and describes its practical impact. It should not simply express a preference about how code looks.
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For example, a comment that a line would be easier to read with a different formatting choice is usually a nit. A comment that a particular input causes a changed function to return the wrong result identifies a condition and a correctness impact, so it merits investigation.
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Start with a reusable instruction
Review only for discrete, actionable issues introduced by this change that meaningfully affect correctness, security, performance, or maintainability. Ignore non-blocking style, formatting, spelling, documentation, and naming preferences unless they obscure meaning or violate a documented project standard. For each finding, explain the triggering condition and impact, and keep the comment focused on one issue. Do not report speculative concerns without evidence in the diff or repository context.
This rubric reflects the Codex review rubric’s guidance to focus on actionable, impactful findings and ignore non-blocking nits. Adjust the issue categories and comment format to fit your project. The exception for documented standards matters: the goal is to suppress subjective preferences, not legitimate conventions or problems that make code hard to understand. OpenAI Codex review rubric
Put durable expectations where the agent can find them
Keep stable review expectations in repository instructions so they are available repeatedly, and add narrower instructions for conventions that apply only to particular files or subsystems. This helps distinguish a documented local requirement from an agent’s generic style preference.
Rank #2
GitHub Copilot instruction locations
GitHub documents .github/copilot-instructions.md for repository-wide guidance and .github/instructions/**/*.instructions.md for path-specific guidance. Repository-wide instructions also apply to code review. GitHub’s documentation lists AGENTS.md as a supported custom instruction source for Copilot cloud agent; do not assume support or precedence is identical for every Copilot feature or other coding agent. GitHub: Adding repository custom instructions for GitHub Copilot
Keep shared and path-specific rules distinct
- Use repository-wide instructions for the review threshold and conventions shared across the project.
- Use path-specific instructions for subsystem or file conventions that would otherwise be easy to mistake for arbitrary style preferences.
- When applying a file name or precedence rule to another agent, check that agent’s current documentation rather than assuming it follows GitHub’s behavior.
Match review depth to change risk
Where the review tool offers a choice of effort, select it according to the change’s risk and complexity, not simply a desire to produce more comments. GitHub describes Copilot’s Lite review as cost-efficient and targeted at glaring issues. Balanced is described as deeper analysis for complex logic, security-sensitive changes, and work spanning services. These are Copilot-specific options, not universal modes available in every agent. GitHub: Using Copilot code review
- For straightforward, low-risk changes, a lighter review may be appropriate when available.
- For complex logic, security-sensitive changes, or cross-service work, use deeper review where the product offers it.
- Do not treat either mode as a substitute for required checks or engineering judgment.
Validate findings instead of treating them as verdicts
AI review is fallible. GitHub cautions that Copilot may miss problems or make mistakes, and recommends carefully validating its feedback and supplementing it with human review. Check whether each finding is supported by the diff and repository context, then run the project’s normal tests and required checks. Reject comments that are speculative or amount only to a non-blocking preference; investigate comments that identify a concrete failure condition or meaningful risk. GitHub: Using Copilot code review
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose configuration by scope and risk
When comparing review configurations, consider how deep the analysis is intended to be and what kinds of changes warrant that depth. When choosing instruction files, consider their scope, which agents can read them, and whether they make local conventions explicit. These choices address different problems: a deeper review setting does not replace clear instructions, and a repository rule does not guarantee that an agent will catch every defect.
Quick Recap
Best Value
| Decision | What to consider |
|---|---|
| Review effort | Intended depth and the change’s complexity or risk; available modes vary by product. |
| Instruction scope | Repository-wide expectations versus conventions for selected paths. |
| Agent coverage | Whether the chosen agent supports the instruction file and how it handles precedence. |
| Human validation | How findings will be checked against the change, project context, and required engineering checks. |
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