code-refinement
SolidImprove code quality: duplication, efficiency, clean code, architectural fit, and error handling
AI & Automation 308 stars
27 forks Updated today MIT
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Quality Score: 96/100
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Documentation 15%
Issue Health 10%
License 10%
Description 5%
Skill Content
## Table of Contents
- [Quick Start](#quick-start)
- [When to Use](#when-to-use)
- [Analysis Dimensions](#analysis-dimensions)
- [Progressive Loading](#progressive-loading)
- [Required TodoWrite Items](#required-todowrite-items)
- [Workflow](#workflow)
- [Tiered Analysis](#tiered-analysis)
- [Cross-Plugin Dependencies](#cross-plugin-dependencies)
# Code Refinement Workflow
Analyze and improve living code quality across six dimensions.
## Quick Start
```bash
/refine-code
/refine-code --level 2 --focus duplication
/refine-code --level 3 --report refinement-plan.md
```
## When To Use
- After rapid AI-assisted development sprints
- Before major releases (quality gate)
- When code "works but smells"
- Refactoring existing modules for clarity
- Reducing technical debt in living code
## When NOT To Use
- Removing
dead/unused code (use conserve:bloat-detector)
## Analysis Dimensions
| # | Dimension | Module | What It Catches |
|---|-----------|--------|----------------|
| 1 | Duplication & Redundancy | `duplication-analysis` | Near-identical blocks, similar functions, copy-paste |
| 2 | Algorithmic Efficiency | `algorithm-efficiency` | O(n^2) where O(n) works, unnecessary iterations |
| 3 | Clean Code Violations | `clean-code-checks` | Long methods, deep nesting, poor naming, magic values |
| 4 | Architectural Fit | `architectural-fit` | Paradigm mismatches, coupling violations, leaky abstractions |
| 5 | Anti-Slop Patterns | `clean-code-checks` | Premature abstraction, ...
Details
- Author
- athola
- Repository
- athola/claude-night-market
- Created
- 6 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
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