I built LlamaPReview to solve a common frustration: most AI code reviewers either require complex setup or don't truly understand project context.
Key differentiators:
1. One-click installation through GitHub Marketplace - no configuration needed
2. Analyzes your entire codebase first to understand:
- Project structure
- Coding patterns
- Naming conventions
- Architecture decisions
3. Completely free with no usage limits
4. Fully automated PR reviews with zero human intervention required
Technical implementation:
- Built on top of llama-github (my open source project)
- Focuses on deep code understanding rather than superficial linting
- Provides context-aware suggestions with explanations
The goal is to handle routine reviews automatically so developers can focus on complex architectural decisions. Currently in production and processing real PRs.
Try it for free: https://github.com/marketplace/llamapreview/
Looking for feedback from the HN community, especially on:
- What features would make this more useful for your workflow?
- How do you currently handle code review automation?
- What aspects of code understanding matter most to you?
I hate to be the compliance guy, but even from a startup perspective you'd at least want to mention what you promise to do here.
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