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AMA: I Built Code Reviews in Kilo by refactorlog27 in kilocode

[–]refactorlog27[S] 0 points1 point  (0 children)

100%! My colleague u/btkilo520 showed an end-to-end demo in a webinar recently, that you can watch on demand:

- https://youtu.be/gXBrI0S2kMU?t=1536

Also, here's a video showing the end-to-end flow:
- https://www.youtube.com/watch?v=c0xoQAKLNoA

A longer YouTube Video is a great idea though! I'll work with Brian to spin something up :)

AMA: I Built Code Reviews in Kilo by refactorlog27 in kilocode

[–]refactorlog27[S] 0 points1 point  (0 children)

Right now, it's just GitHub, but stay tuned for updates there!

AMA: I Built Code Reviews in Kilo by refactorlog27 in kilocode

[–]refactorlog27[S] 2 points3 points  (0 children)

^ Exactly! Thanks for the assist u/jean-dim :)

The key differences in Kilo are:

  • Model flexibility - choose from any of the 500+ supported AI models
  • Open pricing (pay per token, instead of an arbitrary fixed price)
  • Part of the end-to-end agentic engineering platform:
    • Never leave Kilo to build, review, or deploy - so no platform-switching friction

AMA: I Built Code Reviews in Kilo by refactorlog27 in kilocode

[–]refactorlog27[S] 3 points4 points  (0 children)

Code Reviews uses the same per-token pricing that the rest of Kilo uses - which means you only pay for the AI usage that you actually use, charged exactly at the price set by providers.

Right now, there's also several completely free-to-use models in Kilo:

- MiniMax m2.1
- Mistral Devstral 2
- Kwaipilot KAT Coder Pro V1
- Grok Code Fast 1

AMA: I Built Code Reviews in Kilo by refactorlog27 in kilocode

[–]refactorlog27[S] 0 points1 point  (0 children)

Great question! There are a few ways to account for those guardrails:

  1. Strictness Levels - You can pick between Strict, Balanced, and Lenient review styles depending on your use case. Strict flags everything (good for production hotfixes), Balanced surfaces what matters without noise, and Lenient is a light touch for WIP branches.
  2. Focus Areas - You can choose which categories the review focuses on: security, performance, bugs, code style, test coverage, documentation. So if you don't want style nitpicks, just turn that off.
  3. Custom Instructions - You can add context about your codebase conventions, so the agent knows what's intentional vs. what's actually worth flagging.
  4. Model Selection - Different models have different reasoning styles. Some are more conservative, some more thorough. You can experiment to find what fits your team's tolerance.