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Remove AI-generated code slop from branches. Use after AI-assisted coding sessions to clean up defensive bloat, unnecessary comments, type casts, and style inconsistencies. Focuses on identifying and removing AI artifacts that degrade code quality.
npx skill4agent add 89jobrien/steve ai-code-cleanupRemove AI slop from this branchClean up the code in this pull requestRemove unnecessary comments and defensive code from src/// ❌ AI-generated: Obvious comment
// Set the user's name
user.name = name;
// ✅ Clean: Self-documenting code
user.name = name;// ❌ AI-generated: Unnecessary defensive code
function processUser(user) {
try {
if (user && user.name && typeof user.name === 'string') {
return user.name.toUpperCase();
}
return null;
} catch (error) {
console.error(error);
return null;
}
}
// ✅ Clean: Trust the input, handle real errors
function processUser(user) {
return user.name.toUpperCase();
}anyas X@ts-ignore@ts-expect-error// ❌ AI-generated: Type workaround
const data = response.data as any;
const result = processData(data as ProcessedData);
// ✅ Clean: Proper typing
const data = response.data;
const result = processData(data);// ❌ AI-generated: Inconsistent style
const UserData = fetchUser();
var processedData = process(UserData);
let FinalResult = format(processedData);
// ✅ Clean: Consistent style
const userData = fetchUser();
const processedData = process(userData);
const finalResult = format(processedData);git diff $(git merge-base HEAD main)..HEAD --name-onlysrc/auth.js## AI Code Cleanup: src/auth.js
### Removed
- 12 redundant comments explaining obvious code
- 3 comments inconsistent with file style
- 5 over-documented simple operations
### Changes
```javascript
// Before
// Function to validate user email
// Takes email string as input
// Returns boolean indicating validity
function validateEmail(email) {
// Check if email is not empty
if (!email) {
return false; // Return false if empty
}
// Return regex test result
return /^[^\s@]+@[^\s@]+\.[^\s@]+$/.test(email);
}
// After
function validateEmail(email) {
if (!email) return false;
return /^[^\s@]+@[^\s@]+\.[^\s@]+$/.test(email);
}
### Example 2: Defensive Bloat Removal
**Input**: Remove defensive bloat from `src/api/users.js`
**Output**:
```markdown
## AI Code Cleanup: src/api/users.js
### Removed
- 3 unnecessary try/catch blocks
- 8 redundant null checks on validated inputs
- 2 error handlers that can never trigger
### Changes
```javascript
// Before
async function getUser(userId) {
try {
if (!userId || typeof userId !== 'string') {
throw new Error('Invalid userId');
}
const user = await db.users.findById(userId);
if (user && user.id) {
return user;
}
return null;
} catch (error) {
console.error(error);
throw error;
}
}
// After
async function getUser(userId) {
const user = await db.users.findById(userId);
return user || null;
}
## Reference Files
- **`references/REFACTORING_PLAN.template.md`** - Refactoring plan template with code smells, before/after metrics, and rollback strategy
## Best Practices
### Cleanup Guidelines
1. **Preserve Functionality**: Only remove code that doesn't affect behavior
2. **Maintain Style**: Follow existing project conventions
3. **Keep Real Errors**: Don't remove legitimate error handling
4. **Test After Changes**: Always verify code still works
5. **Incremental**: Make changes incrementally, test as you go
### What to Keep
- Legitimate error handling
- Necessary type assertions
- Helpful comments that add context
- Defensive code for untrusted inputs
- Style that matches the codebase
### What to Remove
- Obvious comments
- Unnecessary defensive code
- Type workarounds
- Style inconsistencies
- AI-generated artifacts
## Related Use Cases
- Post-AI coding cleanup
- Code review preparation
- Code quality improvement
- Style standardization
- Removing technical debt