| name | codebase-consolidation |
| description | Analyze, consolidate, and document codebases through multi-perspective analysis. Use when reviewing project structure, planning refactoring, creating documentation, or assessing technical debt. |
Codebase Consolidation & Analysis
Systematically analyze codebases to identify consolidation opportunities, document architecture, and generate actionable insights.
Quick Reference
When to Use
- Starting on a new codebase - Understand structure quickly
- Planning refactoring - Identify consolidation opportunities
- Code review preparation - Comprehensive analysis before changes
- Documentation needs - Generate architecture docs
- Technical debt assessment - Quantify and prioritize improvements
- Onboarding new developers - Create codebase overview
- Pre-release audits - Quality and security review
Don't use for: Single file analysis, quick bug fixes, simple feature additions
Core Purpose
Comprehensive codebase analysis:
- Code Duplication - Find duplicate code for consolidation
- Architectural Analysis - Document system structure and patterns
- Refactoring Opportunities - Identify improvement areas
- Technical Debt Assessment - Quantify and prioritize debt
- Documentation Generation - Create architecture diagrams and docs
- Multi-Perspective Analysis - Review from architect, developer, product views
- Quality Metrics - Complexity, coverage, maintainability
Analysis Dimensions
| Dimension | Focus |
|---|
| Code Duplication | Find duplicate/similar code blocks |
| Architectural Structure | System architecture and component relationships |
| Code Organization | Module structure and separation of concerns |
| Refactoring Opportunities | Large files, complex functions |
| Technical Debt | TODOs, missing tests, outdated deps |
| Quality Metrics | LOC, complexity, coverage |
| Design Patterns | Patterns and anti-patterns in use |
| Cross-Cutting Concerns | Error handling, logging, security |
See analysis-dimensions.md for detailed criteria.
Analysis Workflow
- Discovery - Project structure, file counts, configuration
- Dependency Analysis - cargo tree, outdated, audit
- Duplication Detection - Large files, tech debt markers
- Complexity Analysis - LOC statistics, long functions
- Architecture Mapping - Components, dependencies, data flow
- Quality Assessment - Coverage, linting, formatting
- Documentation Review - Doc generation, API documentation
- Synthesis - Comprehensive report with recommendations
Output Formats
- Executive Summary - Health score, key metrics, priorities
- Architecture Documentation - System diagram, patterns, data flows
- Refactoring Roadmap - Phased plan with tasks and estimates
- Technical Debt Report - Quantified debt, payoff strategy
- Onboarding Document - Developer guide to codebase
See report-templates.md for complete templates.
Best Practices
✓ Start with high-level structure, use automated tools, prioritize findings, provide concrete examples with file paths, estimate effort, consider multiple perspectives
✗ Don't analyze without clear goals, only report problems, provide generic advice, ignore context, recommend big rewrites, overwhelm with detail
See consolidation-patterns.md for refactoring patterns and examples.
