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Greptile learns from your team’s feedback to provide increasingly relevant suggestions. The primary training methods are emoji reactions and explanatory comments.
Learning is continuous. You’ll see noticeable improvement in the first few weeks of consistent feedback, and it keeps getting better over time.

Using Reactions (👍/👎)

Reactions are the fastest way to train Greptile. Every reaction teaches it what matters to your team.
Only 👍 and 👎 train the system. Other emojis (❤️, 🚀, etc.) are treated as neutral.
For 👎 reactions, add a quick comment explaining why:
This helps Greptile understand the context, not just that you disagreed.

Explaining Preferences

While reactions teach what you like, comments teach why. Be specific:
Keep it short:

Tracking Progress

The Analytics dashboard shows how training is going: Low upvote counts? Remind the team to 👍/👎 comments. High addressed rates mean Greptile is learning what matters.

Accelerating Learning

Instead of waiting for organic learning, you can:
  1. Upload style guides - Add your existing docs as custom context
  2. Create explicit rules - Define standards in the dashboard, .greptile/ config, or greptile.json
  3. Use cross-repo context - Share related repository context with repo clusters

What’s next?