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github/refactor-method-complexity-reduce

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refactor-method-complexity-reduce

Refactor given method `${input:methodName}` to reduce its cognitive complexity to `${input:complexityThreshold}` or below, by extracting helper methods.

v1.0Latest
New~1.1kUpdated Jun 26, 2026

Refactor Method to Reduce Cognitive Complexity

Objective

Refactor the method ${input:methodName}, to reduce its cognitive complexity to ${input:complexityThreshold} or below, by extracting logic into focused helper methods.

Instructions

  1. Analyze the current method to identify sources of cognitive complexity:

    • Nested conditional statements
    • Multiple if-else or switch chains
    • Repeated code blocks
    • Multiple loops with conditions
    • Complex boolean expressions
  2. Identify extraction opportunities:

    • Validation logic that can be extracted into a separate method
    • Type-specific or case-specific processing that repeats
    • Complex transformations or calculations
    • Common patterns that appear multiple times
  3. Extract focused helper methods:

    • Each helper should have a single, clear responsibility
    • Extract validation into separate Validate* methods
    • Extract type-specific logic into handler methods
    • Create utility methods for common operations
    • Use appropriate access levels (static, private, async)
  4. Simplify the main method:

    • Reduce nesting depth
    • Replace massive if-else chains with smaller orchestrated calls
    • Use switch statements where appropriate for cleaner dispatch
    • Ensure the main method reads as a high-level flow
  5. Preserve functionality:

    • Maintain the same input/output behavior
    • Keep all validation and error handling
    • Preserve exception types and error messages
    • Ensure all parameters are properly passed to helpers
  6. Best practices:

    • Make helper methods static when they don't need instance state
    • Use null checks and guard clauses early
    • Avoid creating unnecessary local variables
    • Consider using tuples for multiple return values
    • Group related helper methods together

Implementation Approach

  • Extract helper methods before refactoring the main flow
  • Test incrementally to ensure no regressions
  • Use meaningful names that describe the extracted responsibility
  • Keep extracted methods close to where they're used
  • Consider making repeated code patterns into generic methods

Result

The refactored method should:

  • Have cognitive complexity reduced to the target threshold of ${input:complexityThreshold} or below
  • Be more readable and maintainable
  • Have clear separation of concerns
  • Be easier to test and debug
  • Retain all original functionality

Testing and Validation

CRITICAL: After completing the refactoring, you MUST:

  1. Run all existing tests related to the refactored method and its surrounding functionality
  2. MANDATORY: Explicitly verify test results show "failed=0"
    • NEVER assume tests passed - always examine the actual test output
    • Search for the summary line containing pass/fail counts (e.g., "passed=X failed=Y")
    • If the summary shows any number other than "failed=0", tests have FAILED
    • If test output is in a file, read the entire file to locate and verify the failure count
    • Running tests is NOT the same as verifying tests passed
    • Do not proceed until you have explicitly confirmed zero failures
  3. If any tests fail (failed > 0):
    • State clearly how many tests failed
    • Analyze each failure to understand what functionality was broken
    • Common causes: null handling, empty collection checks, condition logic errors
    • Identify the root cause in the refactored code
    • Correct the refactored code to restore the original behavior
    • Re-run tests and verify "failed=0" in the output
    • Repeat until all tests pass (failed=0)
  4. Verify compilation - Ensure there are no compilation errors
  5. Check cognitive complexity - Confirm the metric is at or below the target threshold of ${input:complexityThreshold}

Confirmation Checklist

  • Code compiles without errors
  • Test results explicitly state "failed=0" (verified by reading the output)
  • All test failures analyzed and corrected (if any occurred)
  • Cognitive complexity is at or below the target threshold of ${input:complexityThreshold}
  • All original functionality is preserved
  • Code follows project conventions and standards
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Overall Score

82/100

Grade

B

Good

Safety

88

Quality

84

Clarity

80

Completeness

76

Summary

Refactor a complex method by extracting logic into focused helper methods to reduce cognitive complexity below a specified threshold. The skill guides an agent through identifying complexity sources, extracting validation and case-specific logic, simplifying the main method flow, and verifying refactoring correctness via test execution and complexity measurement.

Detected Capabilities

file readcode analysistest execution verificationcompilation verification

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

reduce cognitive complexityextract helper methodsrefactor methodsimplify nested logicimprove code readability

Use Cases

  • Reduce cognitive complexity in overly nested conditional logic
  • Extract validation logic into separate reusable methods
  • Break down complex transformations into focused helper methods
  • Simplify high-level method orchestration
  • Improve code maintainability and testability through refactoring

Quality Notes

  • Strong emphasis on test verification with explicit failure checking — prevents silent regressions
  • Clear step-by-step approach progresses logically from analysis through implementation to validation
  • Detailed testing checklist (failed=0 requirement) is particularly strong and prevents incomplete verification
  • Best practices section provides concrete guidance on static methods, guard clauses, and return value handling
  • Scope is well-defined: single-method refactoring with clear success criteria (cognitive complexity threshold)
  • No edge case documentation for methods that cannot be effectively refactored (e.g., finite state machines)
  • Does not address scenarios where target complexity threshold is unreachable (e.g., inherently complex algorithms)
  • No guidance on handling breaking changes or API modifications during refactoring
Model: claude-haiku-4-5-20251001Analyzed: Jun 26, 2026

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