Code Improvement & Cleanup Skill

Systematic improvements with multi-persona expertise and safety validation.

Quick Start

Quality improvement

/sc:improve src/ --type quality --safe

Performance optimization

/sc:improve api-endpoints --type performance

Dead code cleanup

/sc:improve src/ --cleanup --type code --safe

Import optimization

/sc:improve --cleanup --type imports

Behavioral Flow

• Analyze - Examine codebase for improvement opportunities

• Plan - Choose approach and activate relevant personas

• Execute - Apply systematic improvements

• Validate - Ensure functionality preservation

• Document - Generate improvement summary

Flags

Flag Type Default Description

--type

string quality quality, performance, maintainability, style, principles, code, imports, files, all

--cleanup

bool false Enable cleanup mode

--safe

bool true Conservative with safety validation

--aggressive

bool false Thorough cleanup (use with caution)

--preview

bool false Show changes without applying

--interactive

bool false Guided decision mode

Personas Activated

• architect - Structure and design improvements

• performance - Optimization expertise

• quality - Code quality and maintainability

• security - Security pattern application

• code-warden - KISS and Purity enforcement (with --type principles)

MCP Integration

PAL MCP (Validation & Analysis)

Tool When to Use Purpose

mcp__pal__consensus

Complex refactors Multi-model validation before major changes

mcp__pal__codereview

Quality assessment Review improvement quality and safety

mcp__pal__thinkdeep

Architecture changes Deep analysis of structural improvements

mcp__pal__precommit

Before commit Validate all changes preserve functionality

mcp__pal__debug

Regression issues Root cause analysis if improvements break things

mcp__pal__challenge

Aggressive mode Critical evaluation of aggressive cleanup decisions

PAL Usage Patterns

Consensus for major refactor

mcp__pal__consensus( models=[ {"model": "gpt-5.2", "stance": "for"}, {"model": "gemini-3-pro", "stance": "against"} ], step="Evaluate: Should we extract this into a separate module?" )

Review after improvements

mcp__pal__codereview( review_type="full", step="Reviewing code improvements", findings="Quality, maintainability, backwards compatibility", relevant_files=["/src/refactored/module.py"] )

Pre-commit validation

mcp__pal__precommit( path="/path/to/repo", step="Validating refactoring changes", confidence="high" )

Rube MCP (Automation & Tracking)

Tool When to Use Purpose

mcp__rube__RUBE_SEARCH_TOOLS

External tools Find linters, formatters, analyzers

mcp__rube__RUBE_MULTI_EXECUTE_TOOL

Notifications Update tickets, notify team

mcp__rube__RUBE_CREATE_UPDATE_RECIPE

Reusable workflows Save improvement patterns

Rube Usage Patterns

Notify team of improvements

mcp__rube__RUBE_MULTI_EXECUTE_TOOL(tools=[ {"tool_slug": "SLACK_SEND_MESSAGE", "arguments": { "channel": "#refactoring", "text": "Completed: Dead code cleanup removed 500 lines" }}, {"tool_slug": "JIRA_UPDATE_ISSUE", "arguments": { "issue_key": "TECH-456", "status": "Done" }} ])

Create improvement report in Notion

mcp__rube__RUBE_MULTI_EXECUTE_TOOL(tools=[ {"tool_slug": "NOTION_CREATE_PAGE", "arguments": { "title": "Refactoring Report - Q4 2025", "content": "## Summary\n- Lines removed: 500\n- Complexity reduced: 25%" }} ])

Evidence Requirements

This skill requires evidence. You MUST:

• Show before/after code comparisons

• Run tests to verify functionality preservation

• Report metrics (lines removed, complexity reduction)

Improvement Types

Quality (--type quality )

• Technical debt reduction

• Code structure improvements

• Readability enhancements

Performance (--type performance )

• Bottleneck resolution

• Algorithm optimization

• Resource efficiency

Maintainability (--type maintainability )

• Complexity reduction

• Documentation improvements

• Modular restructuring

Style (--type style )

• Formatting consistency

• Naming conventions

• Pattern alignment

Principles (--type principles )

• KISS compliance improvements (reduce complexity, extract methods)

• Purity enforcement (separate I/O from logic)

• Guard clause refactoring (reduce nesting)

• Functional core extraction (move I/O to shell layer)

Validators:

Run KISS validation

python .claude/skills/sc-principles/scripts/validate_kiss.py --scope-root . --json

Run Purity validation

python .claude/skills/sc-principles/scripts/validate_purity.py --scope-root . --json

Cleanup Mode (--cleanup )

Code Cleanup (--type code )

• Dead code detection and removal

• Unused variable elimination

• Unreachable code removal

Import Cleanup (--type imports )

• Unused import removal

• Import organization

• Dependency optimization

File Cleanup (--type files )

• Empty file removal

• Orphaned file detection

• Structure optimization

Full Cleanup (--type all )

• Comprehensive cleanup

• All categories combined

• Multi-persona coordination

Safety Modes

Safe Mode (--safe )

• Conservative changes only

• Automatic safety validation

• Preserves all functionality

Aggressive Mode (--aggressive )

• Thorough cleanup

• Framework-aware patterns

• Requires careful review

Examples

Safe Quality Improvement

/sc:improve src/ --type quality --safe

Technical debt reduction with safety validation

Performance Optimization

/sc:improve api-endpoints --type performance --interactive

Guided optimization with profiling analysis

Dead Code Cleanup

/sc:improve src/ --cleanup --type code --safe

Remove unused code with dependency validation

Preview Changes

/sc:improve --cleanup --type imports --preview

Show what would be removed without executing

Tool Coordination

• Read/Grep/Glob - Code analysis

• Edit/MultiEdit - Safe modifications

• TodoWrite - Progress tracking

• Task - Large-scale improvement delegation