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Cursor is the fastest-growing developer tool in history, but most developers use it for the same thing they use autocomplete for: generating new code. The bigger leverage is refactoring. Cursor with the right prompts can systematically improve a legacy codebase, extract duplicated logic, enforce consistent patterns, and modernize outdated code, without introducing regressions. These prompts cover the full refactoring workflow: scoping what to change, making targeted improvements, validating the output, and keeping the codebase consistent as the work progresses.
Stage 1
Unfocused refactoring is how you introduce regressions. These prompts help you identify exactly what to change before touching a single line of code.
Identify refactoring opportunities in a file
Read this file and identify the top five refactoring opportunities, ranked by impact and risk. For each opportunity, describe: what is wrong with the current code, what the improved version would look like, and the risk level of making this change. Do not make any changes yet. File: [PASTE FILE CONTENTS].
Find duplicated logic across the codebase
Analyze the files I have open and identify any logic that is duplicated or nearly duplicated across multiple places. For each duplication, tell me: where it appears, what the extracted abstraction should look like, and whether the differences between versions are meaningful or just incidental. I will review the list before deciding what to extract.
Identify which functions are doing too much
Review this file and flag any functions or methods that violate the single responsibility principle. For each flagged function, explain what responsibilities it currently has and how you would split it into smaller, focused functions. Do not refactor yet, just give me the analysis: [PASTE FILE].
Create a refactoring plan before starting
I want to refactor [DESCRIBE THE CODE AREA OR FEATURE]. Before we change anything, create a refactoring plan that lists: (1) the changes to make in order of dependency, (2) which changes are safe to make independently versus which depend on others, (3) what tests I should run after each step to verify nothing broke. I want a clear sequence before we begin.
Identify naming improvements throughout a file
Read this file and flag any variable, function, or class names that are unclear, misleading, or inconsistent with the naming conventions in the rest of the code. For each one, suggest a better name and explain why the current name is problematic. Do not make changes, just produce the list: [PASTE FILE].
Stage 2
These prompts make specific, well-scoped refactoring changes. Each one targets a single type of improvement to keep changes reviewable.
Extract a function from a long block of code
Extract the following code block into a separate, well-named function. The extracted function should: have a descriptive name that makes its purpose obvious, take only the inputs it needs, return a clear output, and have a JSDoc or equivalent comment if the logic is non-obvious. Show the extracted function and the updated call site: [PASTE CODE BLOCK].
Simplify a complex conditional
Simplify this conditional logic without changing its behavior. Options to consider: extracting conditions into well-named boolean variables, using early returns instead of deep nesting, replacing chained conditionals with a lookup table or map, or restructuring the logic to be easier to follow. Show the before and after with a brief explanation of what you changed: [PASTE CONDITIONAL].
Replace repetition with a reusable abstraction
These code blocks are doing nearly the same thing in multiple places: [PASTE EXAMPLES]. Create a single reusable function or component that covers all cases. Show the abstraction and all the updated call sites. Flag any differences between the current versions that the abstraction needs to handle.
Modernize legacy code to current patterns
Update this code to use current [LANGUAGE/FRAMEWORK] patterns and syntax without changing its behavior. Specific patterns to apply where appropriate: [LIST, e.g. async/await instead of callbacks, optional chaining, destructuring, const/let instead of var, arrow functions, template literals]. Show the modernized version and note each change made: [PASTE CODE].
Improve error handling in a function
Improve the error handling in this function. The current version: [DESCRIBE CURRENT BEHAVIOR]. It should: handle each failure mode explicitly rather than letting errors propagate silently, use descriptive error messages that include the relevant context, and either throw with full context or return a typed error result depending on the pattern used elsewhere in this codebase. Refactored function: [PASTE FUNCTION].
Stage 3
Refactoring without verification is guessing. These prompts help you confirm the changed code is equivalent to the original before it ships.
Write tests for the code before refactoring
Before I refactor this function, write a test suite that captures its current behavior so I can verify the refactored version behaves identically. Include: the happy path, edge cases, and any currently untested scenarios you can infer from the implementation. Use [TEST FRAMEWORK]. Function to test: [PASTE FUNCTION].
Verify the refactored version is equivalent
Here is the original code: [PASTE ORIGINAL]. Here is the refactored version: [PASTE REFACTORED]. Verify that these are logically equivalent by: tracing through at least three distinct inputs, checking that all edge cases are handled the same way, and flagging any paths through the original that the refactored version handles differently. Tell me if they are equivalent or where they diverge.
Check for regressions in connected code
I have refactored [FUNCTION NAME]. Before it was: [PASTE ORIGINAL]. Now it is: [PASTE REFACTORED]. Identify all the places in the codebase where this function is called and check whether the refactored version is a drop-in replacement. Flag any call sites that may behave differently because of: changed parameter signatures, different return values, or modified error behavior.
Review the refactored code for new issues
Review this refactored code for any issues introduced by the change. Look for: new edge cases that were not present in the original, performance regressions, type errors or implicit coercion issues, and anything that would not be caught by the existing tests. Refactored code: [PASTE]. Original code for comparison: [PASTE].
Write the pull request description for a refactor
Write the pull request description for this refactoring change. Include: what changed and why, what the behavior before and after is (identical for pure refactoring), what tests were run or added, and what a reviewer should focus on. Keep it factual and brief. Changes made: [DESCRIBE OR PASTE DIFF SUMMARY].
Stage 4
One-off refactors are less valuable than consistent patterns. These prompts help you apply improvements systematically and document decisions.
Apply the same pattern to multiple similar functions
I refactored [FUNCTION A] to use this pattern: [PASTE REFACTORED VERSION]. Find all other functions in this file that follow the same old pattern and apply the same refactoring to each. Show each refactored function separately so I can review them one at a time. File: [PASTE FILE].
Enforce a naming convention throughout a file
Apply this naming convention to the entire file: [DESCRIBE CONVENTION, e.g. camelCase for variables, PascalCase for components, SCREAMING_SNAKE_CASE for constants, verb-first for function names]. Show every rename needed and the updated file. Do not change any logic, only names: [PASTE FILE].
Write a short ADR for a refactoring decision
Write a brief Architecture Decision Record (ADR) for this refactoring decision. The decision: [DESCRIBE WHAT YOU CHANGED AND WHY]. Format: title, context (why a decision was needed), decision (what was chosen), consequences (what improves, what trade-offs exist). Keep it under 200 words so it is actually read.
Document the patterns to apply in future code
Based on the refactoring we just completed, write a brief coding standards note I can add to CLAUDE.md or a team wiki. It should describe: the pattern we are now using, the pattern it replaces, and a short code example of each so future contributors know what to follow. Keep it concise and practical.
Plan the next refactoring session
Based on the refactoring work we did today, what should be the priority for the next refactoring session in this codebase? Look at what we changed, what we decided not to change, and what other parts of the code have similar issues. Give me a prioritized list of the next five things to tackle, with a one-sentence rationale for each priority.
Cursor has direct access to your actual codebase through its context window and can see the files you have open, the surrounding code, and the project structure. ChatGPT requires you to paste code manually. For refactoring, Cursor is significantly more useful because it can identify issues across multiple files and make changes in context without you copying and pasting everything back and forth.
After. Write tests that capture the current behavior first, then refactor. This is the only way to verify that the refactored version is truly equivalent. If tests do not exist, write them before touching the code. The test-writing prompt in Stage 3 is designed to create a safety net before you make changes.
Accepting changes without reviewing them. Cursor can propose changes across many files at once, and it is easy to accept everything and then discover that a subtle behavioral change was introduced. The validation prompts in Stage 3 address this: always verify equivalence before merging, especially for functions called from many places.
Be specific about scope. Instead of "refactor this file," say "extract the following code block into a function called X without changing anything else." Cursor will sometimes proactively clean up surrounding code if given too broad a directive. The scoping prompts in Stage 1 are designed to define the exact boundary of each change before asking Cursor to execute.
When the code is working and untested. Refactoring untested code introduces risk without a safety net. Also avoid refactoring immediately before a major release, across a file you are in the middle of changing for a feature, or when the benefit is purely aesthetic. The scoping prompts in Stage 1 help you identify which changes are high-value versus low-value.
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