Understanding Vibesweep Reports

Learn how to interpret Vibesweep's analysis results and take action on the findings.

Report Sections

1. Overview Section

📊 Overview: Total files analyzed: 142 # All JS/TS files scanned Total size: 1.2MB # Combined size of analyzed files Total waste: 156KB # Estimated removable code Waste percentage: 13% # Waste / Total size

What to look for:

• Waste > 20%: Significant cleanup opportunity
• Waste > 40%: Critical - immediate action needed
• Waste < 10%: Well-maintained codebase

2. Summary Metrics

📈 Summary: Files with dead code: 23 # Files containing unused code Files with duplications: 8 # Files with copy-pasted code AI-generated files: 45 # Files showing AI patterns

Key insights:

• High dead code count → Need better code review process
• High duplication → Consider extracting shared utilities
• High AI-generated count → Review AI assistant usage patterns

3. Waste Categories

Dead Code

• Unused variables: Declared but never referenced
• Unused functions: Defined but never called
• Unused imports: Imported but not used
• Unreachable code: Code after return statements

Duplication

• Exact matches: Identical code blocks
• Similar patterns: Near-duplicate with minor variations
• Threshold: Blocks > 50 tokens are flagged

AI Patterns

• Verbose conditionals: Over-engineered if statements
• Redundant comments: Comments explaining obvious code
• Boilerplate excess: Unnecessary ceremonial code
• Debug artifacts: Console.logs and debug statements

4. Waste Score Calculation

Waste Score = (Dead Code % × 0.4) + (Duplication % × 0.3) + (AI Score × 0.3)

• 0-20%: Clean file
• 21-40%: Needs attention
• 41-60%: High priority
• 61-100%: Critical cleanup needed

5. AI Detection Score

The AI score (0-100) indicates likelihood of AI generation:

• 0-30: Human-written
• 31-60: Mixed human/AI
• 61-80: Likely AI-generated
• 81-100: Definitely AI-generated

Reading File-Level Reports

src/utils/helpers.js Waste Score: 67% # Overall waste level Dead Code: 45% # Unused code percentage Duplication: 12% # Duplicated code percentage AI Score: 89/100 # AI generation likelihood Patterns: verbose-conditionals # Specific issues found

JSON Output Format

For programmatic processing:

{
  "summary": {
    "totalFiles": 142,
    "totalSize": 1258291,
    "totalWaste": 159872,
    "wastePercentage": 12.7
  },
  "files": [
    {
      "path": "src/utils/helpers.js",
      "wasteScore": 67,
      "deadCode": {
        "ratio": 0.45,
        "unusedFunctions": ["formatDate", "parseJSON"],
        "unusedVariables": ["config", "DEFAULT_TIMEOUT"]
      },
      "duplication": {
        "ratio": 0.12,
        "blocks": [
          {
            "lines": "45-67",
            "duplicateIn": ["src/utils/format.js:23-45"]
          }
        ]
      },
      "aiPatterns": {
        "score": 89,
        "patterns": ["verbose-conditionals", "redundant-comments"]
      }
    }
  ]
}

Taking Action

Priority Matrix

1. Critical (Waste > 60%)

   • Immediate refactoring needed
   • Consider full file rewrite
   • Review with senior developer

2. High (Waste 40-60%)

   • Schedule for next sprint
   • Focus on dead code removal
   • Extract duplicated code

3. Medium (Waste 20-40%)

   • Include in regular maintenance
   • Good for junior developer tasks
   • Document patterns to avoid

4. Low (Waste < 20%)

   • Monitor for regression
   • Address during feature work
   • Use as good examples

Common Fixes

For Dead Code:

// Before
function unused() { return 42; }  // Never called
const config = { debug: true };   // Never used

// After
// Functions and variables removed

For Duplication:

// Before
// File A
const formatUser = (user) => {
  return `${user.firstName} ${user.lastName}`;
};

// File B
const displayName = (person) => {
  return `${person.firstName} ${person.lastName}`;
};

// After
// Shared utility
export const formatFullName = (obj) => {
  return `${obj.firstName} ${obj.lastName}`;
};

For AI Patterns:

// Before (AI-generated)
if (user !== null && user !== undefined && user.id !== null && user.id !== undefined) {
  // Overly verbose null checking
}

// After (Human-optimized)
if (user?.id) {
  // Clean optional chaining
}

Best Practices

1. Run regularly: Weekly scans prevent waste accumulation
2. Set thresholds: Configure acceptable waste levels
3. Track progress: Monitor waste percentage over time
4. Team education: Share reports in code reviews
5. Gradual improvement: Focus on worst offenders first