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Add CodeRabbit AI Review Workflow for Automated Code Reviews #113
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🤖 CodeRabbit AI Review AvailableTo request a code review from CodeRabbit AI, add CodeRabbit will analyze your code and provide feedback on:
Note: Reviews are only performed when |
🔍 Vulnerabilities of
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| digest | sha256:17e54ff5e9a181d1bdbf7334ce9637f9c3934d54a65427ae36a5743f46487f15 |
| vulnerabilities | |
| platform | linux/amd64 |
| size | 218 MB |
| packages | 358 |
📦 Base Image alpine:3
| also known as |
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| digest | sha256:1c4eef651f65e2f7daee7ee785882ac164b02b78fb74503052a26dc061c90474 |
| vulnerabilities |
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- Removed unnecessary blank lines in the workflow YAML file to enhance clarity and maintainability. - Updated the 'summarize' parameter to use an empty string for consistency. These changes streamline the workflow configuration, making it easier to read and manage.
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killev
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Looks Good.



Add CodeRabbit AI Review Workflow for Automated Code Reviews
Introduced a new GitHub Actions workflow for automated code reviews using CodeRabbit AI.
The workflow triggers on pull requests (opened, edited, synchronize) and manual dispatch, allowing for flexible review processes.
Implemented two main jobs: banner posting for onboarding notifications and AI-powered code review execution.
Added functionality to detect missing API keys (CODERABBIT_TOKEN, OPENAI_API_KEY) with setup reminders and documentation links.
Enhanced review process with commit SHA tracking to prevent duplicate reviews for the same commit.
Configured CodeRabbit to focus exclusively on actual problems (bugs, security issues, performance, code quality) while ignoring minor style issues and documentation gaps.
Added concurrency control to cancel in-progress reviews when new commits are pushed.
Implemented custom system message to ensure reviews provide actionable inline comments with structured format (category, current code, suggestion, impact explanation).
Docs: https://wiki.gluzdov.com/doc/coderabbit-review-workflow-setup-6CqNB5aHtY
This integration aims to streamline code review and improve code quality through automated AI analysis while maintaining focus on significant issues only.