Audit Refactoring

Single-Session Refactoring Audit

Pre-Audit Validation

Step 1: Check Thresholds

Run npm run review:check and report results.

• If no thresholds triggered: "⚠️ No review thresholds triggered. Proceed anyway?"
• Continue with audit regardless (user invoked intentionally)

Step 2: Gather Current Baselines

Collect these metrics by running commands:

# SonarQube issues (if manifest exists)
cat docs/analysis/sonarqube-manifest.md 2>/dev/null | head -30 || echo "No SonarQube manifest"

# Circular dependencies
npm run deps:circular 2>&1

# Unused exports
npm run deps:unused 2>&1 | head -30

# Large files (potential god objects)
find app components lib -name "*.ts" -o -name "*.tsx" 2>/dev/null | xargs wc -l 2>/dev/null | sort -n | tail -20

# Duplicate code patterns
grep -rn "TODO\|FIXME\|HACK" --include="*.ts" --include="*.tsx" 2>/dev/null | wc -l

Step 2b: Query SonarCloud for Cognitive Complexity (if MCP available)

If mcp__sonarcloud__get_issues is available:

• Query with types: "CODE_SMELL" and severities: "CRITICAL" to get cognitive complexity violations
• These are the primary refactoring targets (47 CRITICAL as of 2026-01-05 baseline)
• Compare current count against baseline - significant changes indicate code quality trends
• Use issue file paths to prioritize audit focus areas

This provides real-time cognitive complexity data for targeted refactoring.

Step 3: Load False Positives Database

Read docs/audits/FALSE_POSITIVES.jsonl and filter findings matching:

• Category: refactoring
• Expired entries (skip if expires date passed)

Note patterns to exclude from final findings.

Step 4: Check Template Currency

Read docs/templates/MULTI_AI_REFACTORING_PLAN_TEMPLATE.md and verify:

• SonarQube baseline is current (778 issues, 47 CRITICAL)
• Known god objects are listed
• Batch fix opportunities are documented

If outdated, note discrepancies but proceed with current values.

Audit Execution

Focus Areas (5 Categories):

1. God Objects (large files, too many responsibilities)
2. Code Duplication (repeated patterns, copy-paste code)
3. Cognitive Complexity (SonarQube CRITICAL targets)
4. Architecture Violations (layer boundaries, import cycles)
5. Technical Debt Markers (TODOs, FIXMEs, HACKs)

For each category:

1. Search relevant files using Grep/Glob
2. Identify specific issues with file:line references
3. Classify severity: S0 (blocking) | S1 (major friction) | S2 (annoying) | S3 (nice-to-have)
4. Estimate effort: E0 (trivial) | E1 (hours) | E2 (day) | E3 (major)
5. Assign confidence level (see Evidence Requirements below)

Refactoring Targets:

• Files > 300 lines (potential split candidates)
• Functions > 50 lines (complexity risk)
• Components with > 10 props (interface too large)
• Files with > 5 imports from different domains (coupling)
• Circular dependencies (from deps:circular)
• Unused exports (from deps:unused)

Scope:

• Include: app/, components/, lib/, hooks/, functions/
• Exclude: node_modules/, .next/, docs/

Evidence Requirements (MANDATORY)

All findings MUST include:

1. File:Line Reference - Exact location (e.g., lib/utils.ts:45)
2. Code Snippet or Metrics - The actual problematic code or measured metrics (lines, complexity)
3. Verification Method - How you confirmed this is an issue (wc -l, deps:circular, grep)
4. Quantified Impact - Lines of code, number of dependencies, complexity score

Confidence Levels:

• HIGH (90%+): Confirmed by tool (SonarQube, deps:circular, wc -l), verified file exists, metrics match
• MEDIUM (70-89%): Found via pattern search, file verified, but metrics estimated
• LOW (<70%): Pattern match only, needs manual verification

S0/S1 findings require:

• HIGH or MEDIUM confidence (LOW confidence S0/S1 must be escalated)
• Dual-pass verification (re-read the code after initial finding)
• Cross-reference with SonarQube or dependency analysis output

Cross-Reference Validation

Before finalizing findings, cross-reference with:

1. SonarQube manifest - Mark findings as "TOOL_VALIDATED" if SonarQube flagged same issue
2. deps:circular output - Mark architecture findings as "TOOL_VALIDATED" if tool detected cycle
3. deps:unused output - Mark dead code findings as "TOOL_VALIDATED" if tool detected unused export
4. Prior audits - Check docs/audits/single-session/refactoring/ for duplicate findings

Findings without tool validation should note: "cross_ref": "MANUAL_ONLY"

Dual-Pass Verification (S0/S1 Only)

For all S0 (blocking) and S1 (major friction) findings:

1. First Pass: Identify the issue, note file:line and initial evidence
2. Second Pass: Re-read the actual code in context
   • Verify the complexity/coupling issue is real
   • Check for intentional design decisions (documented trade-offs)
   • Confirm file and line still exist
3. Decision: Mark as CONFIRMED or DOWNGRADE (with reason)

Document dual-pass result in finding: "verified": "DUAL_PASS_CONFIRMED" or "verified": "DOWNGRADED_TO_S2"

Output Requirements

1. Markdown Summary (display to user):

## Refactoring Audit - [DATE]

### Baselines

- SonarQube CRITICAL: X issues
- Circular dependencies: X
- Unused exports: X
- Files > 300 lines: X
- TODO/FIXME/HACK markers: X

### Findings Summary

| Severity | Count | Category | Confidence  |
| -------- | ----- | -------- | ----------- |
| S0       | X     | ...      | HIGH/MEDIUM |
| S1       | X     | ...      | HIGH/MEDIUM |
| S2       | X     | ...      | ...         |
| S3       | X     | ...      | ...         |

### Top Refactoring Candidates

1. [file] - X lines, Y responsibilities (S1/E2) - DUAL_PASS_CONFIRMED
2. ...

### False Positives Filtered

- X findings excluded (matched FALSE_POSITIVES.jsonl patterns)

### Quick Wins (E0-E1)

- ...

### Batch Fix Opportunities

- X instances of [pattern] can be auto-fixed
- ...

### Recommendations

- ...

2. JSONL Findings (save to file):

Create file: docs/audits/single-session/refactoring/audit-[YYYY-MM-DD].jsonl

Each line (UPDATED SCHEMA with confidence and verification):

{
  "id": "REF-001",
  "category": "GodObject|Duplication|Complexity|Architecture|TechDebt",
  "severity": "S0|S1|S2|S3",
  "effort": "E0|E1|E2|E3",
  "confidence": "HIGH|MEDIUM|LOW",
  "verified": "DUAL_PASS_CONFIRMED|TOOL_VALIDATED|MANUAL_ONLY",
  "file": "path/to/file.ts",
  "line": 123,
  "title": "Short description",
  "description": "Detailed issue",
  "metrics": { "lines": 450, "functions": 25, "complexity": 45 },
  "recommendation": "How to refactor",
  "batch_fixable": true,
  "evidence": ["code structure info", "wc -l output", "deps:circular output"],
  "cross_ref": "sonarqube|deps_circular|deps_unused|MANUAL_ONLY"
}

3. Markdown Report (save to file):

Create file: docs/audits/single-session/refactoring/audit-[YYYY-MM-DD].md

Full markdown report with all findings, baselines, and refactoring plan.

Post-Audit Validation

Before finalizing the audit:

1. Run Validation Script:

   node scripts/validate-audit.js docs/audits/single-session/refactoring/audit-[YYYY-MM-DD].jsonl
   

2. Validation Checks:

   • All findings have required fields
   • No matches in FALSE_POSITIVES.jsonl (or documented override)
   • No duplicate findings
   • All S0/S1 have HIGH or MEDIUM confidence
   • All S0/S1 have DUAL_PASS_CONFIRMED or TOOL_VALIDATED

3. If validation fails:

   • Review flagged findings
   • Fix or document exceptions
   • Re-run validation

Post-Audit

1. Display summary to user
2. Confirm files saved to docs/audits/single-session/refactoring/
3. Run node scripts/validate-audit.js on the JSONL file
4. Validate CANON schema (if audit updates CANON files):

   npm run validate:canon
   

   Ensure all CANON files pass validation before committing.
5. Update AUDIT_TRACKER.md - Add entry to "Refactoring Audits" table:
   • Date: Today's date
   • Session: Current session number from SESSION_CONTEXT.md
   • Commits Covered: Number of commits since last refactoring audit
   • Files Covered: Number of files analyzed for refactoring
   • Findings: Total count (e.g., "1 S1, 3 S2, 5 S3")
   • Confidence: Overall confidence (HIGH if majority HIGH, else MEDIUM)
   • Validation: PASSED or PASSED_WITH_EXCEPTIONS
   • Reset Threshold: YES (single-session audits reset that category's threshold)
6. Update Technical Debt Backlog - Re-aggregate all findings:

   npm run aggregate:audit-findings
   

   This updates docs/aggregation/MASTER_ISSUE_LIST.md and the Technical Debt Backlog section in ROADMAP.md. Review the updated counts and ensure new findings are properly categorized.
7. Ask: "Would you like me to tackle any of these refactoring tasks now? (Recommend starting with batch fixes)"

Threshold System

Category-Specific Thresholds

This audit resets the refactoring category threshold in docs/AUDIT_TRACKER.md (single-session audits reset their own category; multi-AI audits reset all thresholds). Reset means the commit counter for this category starts counting from zero after this audit.

Refactoring audit triggers (check AUDIT_TRACKER.md):

• 40+ commits since last refactoring audit, OR
• 3+ new complexity warnings, OR
• Circular dependency detected

Multi-AI Escalation

After 3 single-session refactoring audits, a full multi-AI Refactoring Audit is recommended. Track this in AUDIT_TRACKER.md "Single audits completed" counter.

Adding New False Positives

If you encounter a pattern that should be excluded from future audits:

node scripts/add-false-positive.js \
  --pattern "regex-pattern" \
  --category "refactoring" \
  --reason "Explanation of why this is intentional complexity" \
  --source "AI_REVIEW_LEARNINGS_LOG.md#review-XXX"