| name | quality-check |
| description | 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. |
| version | 0.1.0 |
| source | fork |
| checksum | 0fee4661b24036455cab84e6e48678ac7a5cd8a794f10d4550d56452933d8cc6 |
| updated_at | 2026-06-08T02:50:00.000Z |
| layer | quality |
Codex CLI: Invoke when the description matches, or manually with $quality-check. No hooks or background auto-run.
Code Quality Check Skill
When to Use This Skill
Automatically invoke this Skill when:
- User asks to "check code quality", "review this code"
- User mentions refactoring or code improvements
- User wants quality scores or metrics
- Before major refactoring efforts
- During code review processes
- Keywords: "quality", "refactor", "review", "improve code", "code smell"
What This Skill Does
CodeDNA Quality Analyzer provides:
- 6-Dimension Scoring - Comprehensive quality assessment
- Issue Identification - Specific problems with severity levels
- ROI-Optimized Suggestions - High-value refactoring priorities
- PageRank Analysis - Quality hotspot identification
The 6 Quality Dimensions
- Complexity - Cyclomatic complexity, nesting depth
- Maintainability - Code readability, documentation quality
- Modularity - Coupling, cohesion, dependency structure
- Test Coverage - Test quality and coverage metrics
- Documentation - Comment ratio, API docs completeness
- Best Practices - Style guide adherence, pattern usage
Instructions
When this Skill is invoked:
Step 1: Determine Analysis Mode
Ask yourself:
- Is it a single file? → Use
test_quality_simple.py
- Is it a project directory? → Use
project_quality_analyzer.py --mode overview
- Need impact analysis? → Use
project_quality_analyzer.py --mode impact-analysis
Step 2: Resolve Runtime and Execute the Analysis
IMPORTANT: Execute one of these analyzer commands. Prefer python3, fall
back to python, and allow PROJECTMIND_HOME to override the default local
tool path.
Single File Analysis:
PROJECTMIND_HOME="${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" "$PROJECTMIND_HOME/test_quality_simple.py" "[file_path]"
Project Overview:
PROJECTMIND_HOME="${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" "$PROJECTMIND_HOME/project_quality_analyzer.py" --project "[directory_path]" --mode overview
Impact Analysis:
PROJECTMIND_HOME="${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:
## 🔬 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]
:
[ ] [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:
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:
PROJECTMIND_HOME="${PROJECTMIND_HOME:-/Users/WangQiao/claude-enhanced-quality}"
PYTHON_BIN="${PYTHON_BIN:-$(command -v python3 || command -v python || true)}"
"$PYTHON_BIN" "$PROJECTMIND_HOME/project_quality_analyzer.py" --project src/payment --mode overview
You present: Project-wide quality assessment, hotspots, and priority fixes.
Example 3: Impact Analysis
User: "I want to refactor the database layer, what's the impact?"
Execute:
PROJECTMIND_HOME="${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
