For the latest updates and improvements in production, open docs.codacy.com instead.
GitHub integration#
The GitHub integration incorporates Codacy on your existing Git provider workflows by reporting issues and the analysis status directly on your pull requests.
When you add a new repository, Codacy sets the GitHub integration using the default settings for your organization. You can then customize the settings for the repository.
Configuring the GitHub integration#
To configure the GitHub integration, open your repository Settings, tab Integrations.
Depending on the options that you enable, Codacy will automatically update pull requests on GitHub with extra information when accepting pull requests.
Tip
You can apply the default Git provider integration settings to all repositories to ensure that your repositories all share the same settings.
Status checks#
Adds a report to your pull requests showing whether your pull requests and coverage are up to standards or not as configured on the quality gate rules for your repository. You can then optionally block merging pull requests that aren't up to standards.
Important
To get a status for coverage you must also:
- Add coverage to your repository
- Enable the rule Diff coverage is under or Coverage variation is under on the pull request quality gate.
Pull request summary#
This feature is only available on paid plans
Note
This feature is only supported on GitHub.
When enabled, Codacy posts a comment on your pull requests each time a new analysis completes. The comment shows the quality gate result and breaks down issues, metrics (complexity and duplication), and coverage (diff coverage and coverage variation), giving you a full picture of the impact of your changes without leaving GitHub.
Enable AI Reviewer#
When enabled, the AI Reviewer posts a standalone code review on the pull request and adds a trigger section to the pull request summary comment, allowing you to run the reviewer on demand. When disabled, the trigger section does not appear in the pull request summary comment.
The AI Reviewer combines the reliability of deterministic, rule-based static code analysis with the enhanced context and prioritization capabilities of AI. It draws in the necessary context from PR metadata, Jira ticket if integration exists, source code, and Codacy data to ensure the business intent matches the technical outcome, and can catch logic gaps that conventional scanners (and human reviewers) often miss.
It provides feedback on missing or weak tests, complex or duplicated code, and keeps security concerns up to date. Beyond that, it adds contextual insights about whether the changes follow the requirements, business rules, and logic used in the project.
Configure when the AI Reviewer runs using the Run reviewer setting:
| Mode | Behaviour |
|---|---|
| Automatically (first review only) | Codacy runs the reviewer once automatically when the pull request is opened, then requires manual triggering for subsequent updates. |
| Manually | Click Run Reviewer in the pull request summary comment or call our public API to trigger a review on demand. |
Tip
Improve the AI Reviewer results by providing custom instructions. Learn how to do it here.
Issue annotations#
Adds annotations on the lines of the pull request where Codacy finds new issues. Codacy maps the severity of the issues reported by the tools to the severity levels of the annotations. To enable this option, you must enable Status checks first.
Issue summaries#
Shows an overall view of the changes in the pull request, including new issues and metrics such as complexity and duplication. To enable this option, you must enable Status checks first.
Suggested fixes#
This feature is only available on paid plans
Adds comments on the lines of the pull request where Codacy finds new issues with suggestions on how to fix the issues. Codacy doesn't apply any changes automatically. To apply the changes, manually review and accept the suggestions.
See also#
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