Every team has unwritten context — technology preferences, naming conventions, architectural decisions, migration details. Instead of documenting them all upfront, you can teach Kody through natural conversation so future reviews are more relevant and repetitive bad suggestions go away.Documentation Index
Fetch the complete documentation index at: https://docs.kodus.io/llms.txt
Use this file to discover all available pages before exploring further.
How it works
When you talk to Kody in PR comments, it detects when you’re stating codebase context or a team preference and automatically saves it as a Memory. Memories are then applied as high-priority context in all future code reviews and conversations.Explicit teaching
Directly tell Kody to remember something:Implicit learning
State a preference naturally — Kody picks it up:What Kody won’t save
Kody is selective about what becomes a memory:- Temporary instructions (“fix this now”, “skip this for today”)
- Questions (“what’s the deadline?”)
- Debugging chatter (“I see an error”)
- Vague statements without actionable information
- Requests scoped to a single PR or task
Memory scopes
Each memory applies at a specific level:| Scope | Example |
|---|---|
| Directory | ”In src/components/ui, always use our design system tokens” |
| Repository | ”This repo uses hexagonal architecture” |
| Organization | ”All repos use ESLint flat config” |