Optimizing Cursor Rules for Better TypeScript Refactoring in Large Codebases

DeepSeek-V3 is currently punching way above its weight class when it comes to handling the sheer volume of context needed for large-scale TypeScript refactoring in Cursor. I've spent the last few days pitting it against Claude 3.5 Sonnet across a monorepo with over 200k lines of code, and the difference in how they respect .cursorrules is stark.

Sonnet is still the king of "elegant" logic, but it tends to get overconfident in large files, often hallucinating that a type definition exists in a different module when it actually doesn't. DeepSeek, conversely, seems more methodical about scanning the provided context before suggesting a change, which makes it significantly safer for complex refactors where a single missing interface can break the entire build.

The trick to actually getting these models to stop introducing "lazy" patterns (like using any or omitting return types during a refactor) is to move away from generic instructions and use strict, constraint-based rules. If your .cursorrules just says "Use best practices," you're wasting tokens.

I've found that defining a "Refactor Protocol" within the rules works best. Here is the specific prompt block I'm using to force the model to validate types before committing to a change:

# TypeScript Refactor Protocol
- ALWAYS verify the existence of imported types in the target file before modifying signatures.
- NEVER use 'any' during refactoring; if a type is unknown, use 'unknown' and add a TODO comment.
- When renaming a type or interface, scan the entire workspace for references using the codebase index before applying the change.
- Prefer 'Readonly' and 'const' assertions for configuration objects to prevent side-effect bugs.
- If a refactor changes a public API, explicitly list the affected files in the response.

Performance-wise, I noticed a massive dip in "hallucinated imports" when I switched the model to DeepSeek-V3 for the initial analysis phase, then swapped back to Sonnet for the actual code implementation. Sonnet writes cleaner, more idiomatic TS, but DeepSeek is better at the "mapping" phase of a refactor.

The Trade-offs I've observed:

Claude 3.5 Sonnet
Pros: Unmatched intuition for design patterns; writes extremely concise code; understands nuance in complex generics.
Cons: Prone to "skipping" sections of code in large files (the dreaded // ... rest of code here comments); occasionally ignores negative constraints in rules.

DeepSeek-V3
Pros: Incredible adherence to strict formatting rules; better at cross-referencing multiple files without getting lost; significantly cheaper/faster if using the API.
Cons: Can sometimes be too verbose in its explanations; occasionally misses the "spirit" of a refactor by being too literal with the instructions.

If you're dealing with a codebase where types are heavily nested or you're using complex mapped types, don't rely on the default AI behavior. I've seen a 30% reduction in "type error loops" (where the AI fixes one error but introduces another) just by adding a rule that forces the model to "think" about the type dependency graph before writing a single line of code.

For those struggling with the AI deleting necessary boilerplate during refactors, try adding this to your rules:

- When refactoring, maintain all existing JSDoc comments and decorators.
- Do not omit unchanged code blocks unless specifically asked for a diff.

This stops the model from trying to be "helpful" by shortening the file, which usually just results in you having to manually merge the code back in.