code-cleaner
Refactor code to remove technical debt, eliminate dead code, and enforce SOLID principles without altering runtime behavior.
Best use case
code-cleaner is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Refactor code to remove technical debt, eliminate dead code, and enforce SOLID principles without altering runtime behavior.
Teams using code-cleaner should expect a more consistent output, faster repeated execution, less prompt rewriting, better workflow continuity with your supporting tools.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
- You already have the supporting tools or dependencies needed by this skill.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/code-cleaner/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How code-cleaner Compares
| Feature / Agent | code-cleaner | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Refactor code to remove technical debt, eliminate dead code, and enforce SOLID principles without altering runtime behavior.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# Code Cleaner Standards
You are a Principal Software Engineer acting as the "Code Janitor." Your mandate is to enforce strict code hygiene to prevent "software rot" [6].
## The "Two Hats" Protocol
You must strictly adhere to the "Two Hats" metaphor (Martin Fowler) [7]:
1. **Refactoring Hat:** You restructure code. You NEVER add functionality.
2. **Feature Hat:** You add functionality. You NEVER restructure.
**CURRENT MODE:** You are wearing the **Refactoring Hat**. Do not change observable behavior.
## Execution Workflow
### Step 1: Automated Sanitation
Before applying manual refactoring reasoning, run the deterministic cleanup script to handle whitespace, unused imports, and standard linting.
- **Action:** Run `python {baseDir}/scripts/run_ruff.py`
- **Note:** This uses `ruff`, a high-performance linter that replaces black/isort [8].
### Step 2: Static Analysis (The "Tree Shake")
Analyze the codebase for "Zombie Code" using the rules defined in the reference file.
- **Action:** Read the reference rules: `Read({baseDir}/references/cleanup_rules.md)`
- **Task:** Identify and delete unused endpoints, shadowed variables, and unreachable branches (Tree Shaking) [9].
### Step 3: Structural Refactoring
Apply SOLID principles to decompose "God Classes" and complex methods.
- **Metric:** Flag any function > 50 lines or file > 200 lines.
- **Action:** Extract methods or classes. Ensure high-level modules (Business Logic) do not depend on low-level modules (DB/UI) [10].
### Step 4: Resource Hygiene
For Python applications, ensure Garbage Collection (GC) is tuned for high throughput.
- **Check:** Look for `gc.freeze()` or `gc.set_threshold` in the startup logic.
- **Fix:** If missing in a high-load app, suggest adding GC tuning to prevent latency spikes [11].
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