In general, Codebuff works quite well in larger projects. For example, we've pulled Codebuff into the VSCode repo (millions of lines of code) and have had no issues in our testing. That said, if you're noticing Codebuff getting stuck/forgetting context too soon or using a ton of credits, here are some tips to help you mitigate those issues.

When working with large codebases, you can start Codebuff from specific directories to maintain focus:

cd backend
codebuff

Or equivalently without changing directories:

codebuff --cwd backend

This helps Codebuff concentrate on relevant files and provide more targeted assistance.

For large projects:

• Create separate knowledge.md files in key directories, like so:

  text

  services/
  auth-service/
      knowledge.md
      src/
  user-service/
      knowledge.md
      src/
  api-gateway/
      knowledge.md
      src/

• Focus each knowledge file on its directory's specific concerns

• Link related concepts across knowledge files

• Keep root knowledge.md for project-wide concepts

When working with large codebases:

• Be specific about file locations
• Reference related files explicitly
• Break large changes into smaller, focused requests
• Use the --max mode for better context understanding by loading more files

• Leverage your .codebuffignore and .gitignore files to exclude irrelevant directories
• Start in subdirectories when possible
• Break large refactoring tasks into smaller chunks
• Let Codebuff handle file discovery instead of listing all files