# Quality Check

> This skill should be used when the user asks to "check code quality", "score this code", "find quality hotspots", "prioritize refactoring", "analyze technical debt", "run CodeDNA", or assess maintainability, complexity, modularity, tests, documentation, and best practices.

- Skill: `materialofair/quality-check` (Agent Skill, multi-file: 8 files)
- Install (CLI): `npx skillmds@latest add materialofair/quality-check`
- Raw SKILL.md: https://api.skillmd.com/api/skills/materialofair/quality-check/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: materialofair (https://skillmd.com/u/materialofair)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/materialofair/quality-check

---



> Codex CLI: Invoke when the description matches, or manually with `$quality-check`. No hooks or background auto-run.

# Code Quality Check Skill

## When to Use This Skill

Automatically invoke this Skill when:
- User asks to "check code quality", "review this code"
- User mentions refactoring or code improvements
- User wants quality scores or metrics
- Before major refactoring efforts
- During code review processes
- Keywords: "quality", "refactor", "review", "improve code", "code smell"

## What This Skill Does

**CodeDNA Quality Analyzer** provides:
1. **6-Dimension Scoring** - Comprehensive quality assessment
2. **Issue Identification** - Specific problems with severity levels
3. **ROI-Optimized Suggestions** - High-value refactoring priorities
4. **PageRank Analysis** - Quality hotspot identification

## The 6 Quality Dimensions

1. **Complexity** - Cyclomatic complexity, nesting depth
2. **Maintainability** - Code readability, documentation quality
3. **Modularity** - Coupling, cohesion, dependency structure
4. **Test Coverage** - Test quality and coverage metrics
5. **Documentation** - Comment ratio, API docs completeness
6. **Best Practices** - Style guide adherence, pattern usage

## Instructions

When this Skill is invoked:

### Step 1: Determine Analysis Mode

Ask yourself:
- Is it a **single file**? → Use `test_quality_simple.py`
- Is it a **project directory**? → Use `project_quality_analyzer.py --mode overview`
- Need **impact analysis**? → Use `project_quality_analyzer.py --mode impact-analysis`

### Step 2: Resolve Runtime and Execute the Analysis

**IMPORTANT**: Execute one of these analyzer commands. Prefer `python3`, fall
back to `python`, and allow `PROJECTMIND_HOME` to override the default local
tool path.

**Single File Analysis**:
```bash
PROJECTMIND_HOME="${PROJECTMIND_HOME:-/Users/WangQiao/claude-enhanced-quality}"
PYTHON_BIN="${PYTHON_BIN:-$(command -v python3 || command -v python || true)}"
if [ -z "$PYTHON_BIN" ]; then
  echo "CodeDNA error: no python3 or python interpreter found" >&2
  exit 1
fi
"$PYTHON_BIN" "$PROJECTMIND_HOME/test_quality_simple.py" "[file_path]"
```

**Project Overview**:
```bash
PROJECTMIND_HOME="${PROJECTMIND_HOME:-/Users/WangQiao/claude-enhanced-quality}"
PYTHON_BIN="${PYTHON_BIN:-$(command -v python3 || command -v python || true)}"
if [ -z "$PYTHON_BIN" ]; then
  echo "CodeDNA error: no python3 or python interpreter found" >&2
  exit 1
fi
"$PYTHON_BIN" "$PROJECTMIND_HOME/project_quality_analyzer.py" --project "[directory_path]" --mode overview
```

**Impact Analysis**:
```bash
PROJECTMIND_HOME="${PROJECTMIND_HOME:-/Users/WangQiao/claude-enhanced-quality}"
PYTHON_BIN="${PYTHON_BIN:-$(command -v python3 || command -v python || true)}"
if [ -z "$PYTHON_BIN" ]; then
  echo "CodeDNA error: no python3 or python interpreter found" >&2
  exit 1
fi
"$PYTHON_BIN" "$PROJECTMIND_HOME/project_quality_analyzer.py" --file "[file_path]" --mode impact-analysis
```

If `$PYTHON_BIN` is empty, report that no Python interpreter was found and fall
back to direct local inspection with `rg`, `rg --files`, targeted reads, and the
repo's own test/lint commands.

### Step 3: Present Results

Format the output as:

```markdown
## 🔬 Code Quality Analysis

**Target**: [File/Project Path]
**Overall Score**: XX/100 [🟢/🟡/🔴]

### 6-Dimension Breakdown

| Dimension | Score | Status | Key Insights |
|-----------|-------|--------|--------------|
| Complexity | XX/100 | 🟢/🟡/🔴 | [Main issue] |
| Maintainability | XX/100 | 🟢/🟡/🔴 | [Main issue] |
| Modularity | XX/100 | 🟢/🟡/🔴 | [Main issue] |
| Test Coverage | XX/100 | 🟢/🟡/🔴 | [Main issue] |
| Documentation | XX/100 | 🟢/🟡/🔴 | [Main issue] |
| Best Practices | XX/100 | 🟢/🟡/🔴 | [Main issue] |

### 🔴 Critical Issues (Fix Immediately)
1. **[Issue Name]** - [File:Line]
   - Impact: [High/Medium/Low]
   - Explanation: [What's wrong]
   - Fix: [Specific solution]

### 🟡 Important Issues (Fix This Sprint)
1. **[Issue Name]** - [File:Line]
   - Impact: [explanation]
   - Suggested approach: [how to fix]

### 💡 Refactoring Priorities (ROI-Optimized)

Based on PageRank and quality analysis:

1. **[Module/File Name]** (ROI: High)
   - Current Score: XX/100
   - Effort: [X hours]
   - Benefit: [Specific improvements]
   - Priority: P0/P1/P2

2. **[Module/File Name]** (ROI: Medium)
   - [Details...]

### 📊 Quality Hotspots

Files that would benefit most from refactoring:
- [File 1]: Score XX, high dependency count
- [File 2]: Score XX, complex and frequently changed
- [File 3]: Score XX, critical business logic

### 🎯 Recommended Actions

**Immediate (This Week)**:
- [ ] [Specific action with file:line]
- [ ] [Specific action with file:line]

**Short-term (This Sprint)**:
- [ ] [Refactoring task]
- [ ] [Testing improvement]

**Long-term (Next Quarter)**:
- [ ] [Architecture improvement]
- [ ] [Technical debt reduction]
```

### Step 4: Provide Context

Explain:
- Why these scores matter
- Business impact of the issues
- Risk of not fixing critical problems
- Expected improvement from suggested changes

## Examples

### Example 1: Single File Review
**User**: "Check the quality of src/auth/login.ts"

**Execute**:
```bash
PROJECTMIND_HOME="${PROJECTMIND_HOME:-/Users/WangQiao/claude-enhanced-quality}"
PYTHON_BIN="${PYTHON_BIN:-$(command -v python3 || command -v python || true)}"
"$PYTHON_BIN" "$PROJECTMIND_HOME/test_quality_simple.py" src/auth/login.ts
```

**You present**: 6-dimension scores, specific issues, and refactoring suggestions.

### Example 2: Project Overview
**User**: "How's the code quality of my payment module?"

**Execute**:
```bash
PROJECTMIND_HOME="${PROJECTMIND_HOME:-/Users/WangQiao/claude-enhanced-quality}"
PYTHON_BIN="${PYTHON_BIN:-$(command -v python3 || command -v python || true)}"
"$PYTHON_BIN" "$PROJECTMIND_HOME/project_quality_analyzer.py" --project src/payment --mode overview
```

**You present**: Project-wide quality assessment, hotspots, and priority fixes.

### Example 3: Impact Analysis
**User**: "I want to refactor the database layer, what's the impact?"

**Execute**:
```bash
PROJECTMIND_HOME="${PROJECTMIND_HOME:-/Users/WangQiao/claude-enhanced-quality}"
PYTHON_BIN="${PYTHON_BIN:-$(command -v python3 || command -v python || true)}"
"$PYTHON_BIN" "$PROJECTMIND_HOME/project_quality_analyzer.py" --file src/core/database.ts --mode impact-analysis
```

**You present**: Dependency analysis, affected files, risk assessment, and refactoring plan.

## Quality Thresholds

Scoring system:
- **🟢 80-100**: Good quality, minor improvements only
- **🟡 60-79**: Acceptable, needs improvement
- **🔴 <60**: Poor quality, refactoring required

## ROI Calculation

Refactoring priority is based on:
- **Quality Score** (lower = higher priority)
- **PageRank** (higher = more important)
- **Dependency Count** (higher = more impact)
- **Change Frequency** (higher = more value)

## Integration with ProjectMind

For project-level analysis, the system uses:
- **Knowledge Graph** - Deep project understanding
- **Dependency Mapping** - Complete relationship analysis
- **Historical Data** - Evolution patterns and trends

## Important Notes

- **Always execute** the Python command, don't guess scores
- **Explain the "why"** behind each issue
- **Prioritize by ROI**, not just severity
- **Provide specific fixes**, not generic advice
- **Consider business context** in recommendations

## Common Quality Issues

### Complexity Issues
- High cyclomatic complexity (>10)
- Deep nesting (>4 levels)
- Long functions (>50 lines)
- God classes/objects

### Maintainability Issues
- Poor naming conventions
- Missing documentation
- Magic numbers/strings
- Code duplication

### Modularity Issues
- High coupling
- Low cohesion
- Circular dependencies
- Tight integration

### Testing Issues
- Low coverage (<80%)
- Missing edge cases
- Flaky tests
- No integration tests

## Prerequisites

- Python environment with CodeDNA installed
- Access to project files
- ProjectMind/CodeDNA tools installed at `/Users/WangQiao/claude-enhanced-quality`
  or another path supplied through `PROJECTMIND_HOME`

## Performance

- **Single File**: <5 seconds
- **Project Overview**: 10-30 seconds
- **Impact Analysis**: 15-45 seconds