kodo/reviewer

Table of Contents

⚠️ Limitations & Best Practices

🚧 Limitations

🧠 Context & Understanding
🔄 Process Constraints

✅ Best Practices

📝 Writing PRs for Better AI Review
🤝 Working with AI Comments
🔒 Security

⚠️ Limitations & Best Practices

🚧 Limitations

🧠 Context & Understanding

No business logic awareness — AI only sees code, not product requirements
Limited context window — the model has its own context window, which can hold a limited amount of information
No decision history — does not store the history of previous executions, only reads existing information in Pull Request
Hallucinations — may confidently suggest incorrect solutions or non-existent APIs
Large PR degradation — review quality drops significantly for PRs with 1000+ lines changed

🔄 Process Constraints

Does not replace humans — final decision always belongs to the author and human reviewer
Slower on large PRs — response time grows with the size of changes
No memory between PRs — each review starts from scratch with no prior context

✅ Best Practices

📝 Writing PRs for Better AI Review

Keep PRs small and focused — one logical change per PR, ideally under 400 lines
Write a clear PR description — explain what and why, not just what changed
Split refactoring from feature changes — mixed PRs confuse both AI and humans

🤝 Working with AI Comments

Treat AI comments as suggestions, not mandates — use your judgment
Verify all suggested code before applying — AI can introduce bugs
Use @kodobot in comments to ask follow-up questions about specific lines
Don't blindly resolve AI comments — acknowledge or explain why you disagree
Re-trigger review after major changes by pushing a new commit

🔒 Security

Never put secrets in PR descriptions or comments — AI logs may capture them
Audit AI comments on security-sensitive PRs (auth, crypto, infra) with extra care

🤖 Kodo AI Reviewer

What is Kodo?

📚 Gitea

👩‍💻 Developer

🧑‍🔧 Tech Lead

📚 Bitbucket

👩‍💻 Developer

🧑‍🔧 Tech Lead

📚 Local Kodo

Local Kodo Tool
- Overriding Local Settings