Score Analysis Publish

分析班级考试成绩，生成可视化图表和分析报告，支持多次成绩纵向对比和同层次班级横向对比。

Score Analysis Skill

AI-powered class score analysis tool that generates visualized charts and professional reports. Supports longitudinal comparison across multiple exams and horizontal comparison with peer classes.

Features

• 📊 Auto-detect Excel/CSV headers (supports merged cells, mixed Chinese/English)
• 📈 Multi-dimensional analysis (horizontal & vertical comparison)
• 🎯 Critical student identification (near pass lines)
• 📉 Subject imbalance diagnosis
• 📋 Grouped radar charts by student type
• 📄 Professional Word report with charts
• 🎨 Customizable school branding

Workflow

1. Data Reading & Validation

• Auto-detect header structure
• Extract fields: student ID, name, class, total score, subject scores, rankings
• Output standardized JSON

2. Data Verification (Required)

After reading data, must send to user for verification before analysis:

Submit verification content:

• Average score per subject per class
• Number of students per class
• Total score average
• Special notes (absences, anomalies)

⚠️ Analysis can only proceed after user confirmation!

3. Analysis Dimensions

Horizontal Comparison (Peer Classes)

• Total score average comparison
• Subject average comparison
• Score segment distribution
• Special control line / undergraduate line pass rates
• Top student distribution

Vertical Comparison (Time Dimension)

• Class average score trends
• Pass count changes
• Student ranking fluctuations
• Subject score changes

Individual Analysis

• Student score volatility (stability)
• Subject imbalance diagnosis
• Progress/regression attribution
• Critical student identification (within X points of pass line)

4. Chart Generation

Grouped Radar Charts (by student type)

• Special control line critical students → radar chart (within 10 points, max 5)
• Undergraduate line critical students → radar chart (max 5)
• Subject-imbalanced students → radar chart (highest imbalance index, max 5)

Other Charts

• Subject average score bar chart
• Class average comparison chart
• Score segment distribution chart

5. Report Output

Generate Word format analysis report including:

• School logo, header/footer
• Three-line tables (research style)
• Embedded charts
• Highlight boxes (emphasize conclusions)

6. Presentation PPT (Optional)

Call pptx-master skill to create presentation PPT.

Subject Score Rules

Default Rules

• Chinese, Math, English, Physics: Use raw scores
• Chemistry, Biology, Politics, Geography: Use adjusted scores
• Total score: Default to adjusted total score

Special Cases

• When adjusted/raw scores are in same column (e.g., 85(92) format), ask user to confirm
• If table only has raw scores, use raw scores

Data Processing Rules

Absence/Makeup Handling

• Marks like /, 缺, 缓, 缓考, 0, blank are treated as absence
• Absent students excluded from average calculation

Score Lines

• Special control line, undergraduate line provided by user (may be image)
• May vary per exam, needs individual confirmation

Peer Classes

• Specified by user during analysis
• Must ask if not specified

Student Mobility

• Transferred students excluded from individual analysis

Output Files

• *_standardized.json - Standardized data
• *_analysis.json - Analysis results
• charts/ - Charts directory
• *_report.docx - Analysis report
• *_presentation.pptx - Presentation PPT (optional)

Directory Structure

score-analysis/
  SKILL.md                        # Skill description
  scripts/
    create_template.py            # Template generator
    generate_report_from_template.py  # Report from template
    generate_radar_charts.py      # Grouped radar charts
    generate_report.py            # Direct report generation
  references/
    analysis_framework.md         # Analysis framework
  assets/
    report_template.docx          # Word report template
  examples/
    sample_data.json              # Sample data for testing

Requirements

pip install python-docx matplotlib pandas numpy openpyxl

License

MIT