Tech Debt Mode

Identify, catalog, and eliminate technical debt.

Core Philosophy

“Deletion is the most powerful refactoring.”

The 40% Rule: In AI-assisted coding, expect to spend 30-40% of your time on code health—reviews, smell detection, and refactoring. Without this investment, vibe-coded bases accumulate invisible debt that slows agents and breeds bugs. Schedule regular code health passes, not just reactive fixes.

Every line of code:

• Must be understood
• Must be tested
• Must be maintained
• Can contain bugs

Less code = less of all the above.

Debt Indicators to Find

Process

1. Scan

Search for debt indicators across the codebase:

• Grep for TODO/FIXME comments
• Find functions over threshold length
• Identify files with type errors
• Check for unused exports

2. Categorize

For each finding, assess:

• Severity: How bad is this?
• Effort: How hard to fix?
• Risk: What could go wrong?

3. Prioritize

Focus on:

• 🎯 Quick Wins – Low effort, high impact
• 🔒 Safety First – Fix risky debt before adding features
• 📍 Hot Paths – Prioritize frequently-touched code

4. Fix or Document

• Simple fixes: Just do it (with tests)
• Complex fixes: Create a plan for later

Quick Win Examples

# Before: Dead import
from typing import List, Dict, Optional  # Only Optional used

# After
from typing import Optional

# Before: Bare except
try:
    data = fetch()
except:
    pass

# After: Specific exception
try:
    data = fetch()
except ConnectionError:
    logger.warning("Failed to fetch data, using cache")
    data = get_cached()

Tech Debt Report Format

## Tech Debt Analysis

### Summary

- **Total issues found**: X
- **Critical**: X (fix immediately)
- **Quick wins**: X (easy to fix)
- **Requires planning**: X (complex)

### Findings

#### Critical 🔴

| Location     | Type     | Issue                     | Effort |
| ------------ | -------- | ------------------------- | ------ |
| `file.py:42` | security | bare except hiding errors | Low    |

#### Quick Wins 🎯

| Location      | Type   | Issue             | Effort |
| ------------- | ------ | ----------------- | ------ |
| `utils.py:10` | unused | import never used | Low    |

#### Requires Planning 📋

| Location | Type        | Issue              | Why Complex              |
| -------- | ----------- | ------------------ | ------------------------ |
| `api.py` | duplication | 3 similar handlers | Needs abstraction design |

### Recommendations

[Suggested order of tackling debt]

### Fixed This Session

[List of debt items resolved]

When Fixing Debt

• ✅ Run tests after each change
• ✅ Keep changes atomic and focused
• ✅ Verify no regressions
• ❌ Don’t mix debt fixes with new features
• ❌ Don’t “refactor” working code without reason

Safe Deletion Patterns

Before removing code, verify it’s unused:

# Check for usages
ag "function_name" --python

# Check imports
ag "from module import function_name"

Watch for code that might be used dynamically:

# ✅ Safe to delete: unused import
from typing import List  # 'List' never used in file

# ✅ Safe to delete: unused variable
result = calculate()  # 'result' never read
log(value)  # This is the actual intent

# ✅ Safe to delete: dead branch
if False:  # Will never execute
    do_something()

# ⚠️ Verify first: might be used dynamically
def _helper():  # Underscore suggests private, but check usages
    pass

# ❌ Don't delete without checking: exported function
def public_api():  # Might be called by external code
    pass

Also watch for:

• Dynamically called code (getattr, eval)
• Reflection-based frameworks
• External API contracts
• CLI entry points

Cleaning Checklist

- [ ] Unused imports removed
- [ ] Unused variables removed
- [ ] Dead functions removed
- [ ] Commented-out code removed
- [ ] Debug statements removed
- [ ] Duplicate code consolidated
- [ ] Tests still pass
- [ ] Types still check

Debt Prevention Tips

To prevent future debt:

• Add TODO with issue tracker link: # TODO(JIRA-123): refactor after migration
• Use type hints from the start
• Write tests before marking done
• Review for simplification opportunities

“The best code is no code at all.”