--- name: learn:analytics description: Display learning analytics dashboard with pattern progress, skill effectiveness, and trends delegates-to: autonomous-agent:orchestrator --- # Learning Analytics Dashboard Display comprehensive analytics about the autonomous agent's learning progress, including: - **Pattern Learning Progress**: Quality trends, learning velocity, improvement rates - **Skill Effectiveness**: Top performing skills, success rates, quality contributions - **Agent Performance**: Reliability scores, efficiency ratings, delegation patterns - **Skill Synergies**: Best skill combinations and their effectiveness - **Prediction System**: Accuracy metrics and model performance - **Cross-Project Learning**: Universal patterns and knowledge transfer - **Learning Insights**: Actionable recommendations and trend analysis ## Execution Generate and display the learning analytics report: ```bash # Auto-detects plugin path whether in development or installed from marketplace python /lib/learning_analytics.py show --dir .claude-patterns ``` ## Output Format The command produces a comprehensive terminal dashboard with: 1. **Overview Section**: Total patterns, quality scores, success rates 2. **Quality Trend Chart**: ASCII visualization of quality progression over time 3. **Learning Velocity**: Improvement rates and trajectory analysis 4. **Top Performing Skills**: Rankings by success rate and quality contribution 5. **Top Performing Agents**: Rankings by reliability and efficiency 6. **Skill Synergies**: Best skill combinations discovered 7. **Prediction System Status**: Accuracy and model training metrics 8. **Cross-Project Learning**: Universal pattern statistics 9. **Learning Patterns**: Fastest and slowest learning areas 10. **Key Insights**: Actionable recommendations based on data ## Example Output ``` +===========================================================================+ | LEARNING ANALYTICS DASHBOARD - ENHANCED SYSTEM v3.0 | +===========================================================================+ 📊 OVERVIEW --------------------------------------------------------------------------- Total Patterns Captured: 156 Overall Quality Score: 88.5/100 Success Rate: 92.3% Recent Quality: 91.2/100 (+2.7) Activity (Last 7 days): 12 patterns Activity (Last 30 days): 48 patterns 📈 QUALITY TREND OVER TIME --------------------------------------------------------------------------- 95.0 | ██████████| | ████████████████| | ████████████████████ | | ████████████████████ | 87.5 | ████████████████ | | ████████████ | | ████████ | | ████████ | 80.0 |████ | +------------------------------------------------------+ 106 -> 156 Trend: IMPROVING 🚀 LEARNING VELOCITY --------------------------------------------------------------------------- Weeks Analyzed: 8 Early Average Quality: 85.3/100 Recent Average Quality: 91.2/100 Total Improvement: +5.9 points Improvement Rate: 0.74 points/week Trajectory: ACCELERATING Acceleration: +0.52 (speeding up!) ⭐ TOP PERFORMING SKILLS --------------------------------------------------------------------------- 1. code-analysis Success: 94.3% Quality: 18.5 2. quality-standards Success: 92.1% Quality: 17.8 3. testing-strategies Success: 89.5% Quality: 16.2 4. security-patterns Success: 91.0% Quality: 15.9 5. pattern-learning Success: 88.7% Quality: 15.1 🤖 TOP PERFORMING AGENTS --------------------------------------------------------------------------- 1. code-analyzer Reliability: 96.9% Efficiency: 1.02 2. quality-controller Reliability: 95.2% Efficiency: 0.98 3. test-engineer Reliability: 93.5% Efficiency: 0.89 4. documentation-generator Reliability: 91.8% Efficiency: 0.95 5. frontend-analyzer Reliability: 90.5% Efficiency: 1.05 🔗 SKILL SYNERGIES (Top Combinations) --------------------------------------------------------------------------- 1. code-analysis + quality-standards Score: 8.5 Uses: 38 Quality: 92.3 Success: 97.8% [HIGHLY_RECOMMENDED] 2. code-analysis + security-patterns Score: 7.2 Uses: 28 Quality: 91.0 Success: 96.4% [HIGHLY_RECOMMENDED] 🎯 PREDICTION SYSTEM STATUS --------------------------------------------------------------------------- Status: ACTIVE Models Trained: 15 skills Prediction Accuracy: 87.5% [PASS] High accuracy - automated recommendations highly reliable 🌐 CROSS-PROJECT LEARNING --------------------------------------------------------------------------- Status: ACTIVE Universal Patterns: 45 Avg Transferability: 82.3% [PASS] Knowledge transfer active - benefiting from other projects 💡 KEY INSIGHTS --------------------------------------------------------------------------- [PASS] Learning is accelerating! Quality improving at 0.74 points/week and speeding up [PASS] Recent performance (91.2) significantly better than historical average (88.5) [PASS] Highly effective skill pair discovered: code-analysis + quality-standards (8.5 synergy score) [PASS] Prediction system highly accurate (87.5%) - trust automated recommendations [PASS] Fastest learning in: refactoring, bug-fix +===========================================================================+ | Generated: 2025-10-23T14:30:52.123456 | +===========================================================================+ ``` ## Export Options ### Export as JSON ```bash # Auto-detects plugin path python /lib/learning_analytics.py export-json --output data/reports/analytics.json --dir .claude-patterns ``` ### Export as Markdown ```bash # Auto-detects plugin path python /lib/learning_analytics.py export-md --output data/reports/analytics.md --dir .claude-patterns ``` ## Usage Scenarios ### Daily Standup Review learning progress and identify areas needing attention: ```bash /learning-analytics ``` ### Weekly Review Export comprehensive report for documentation: ```bash # Auto-detects plugin path python /lib/learning_analytics.py export-md --output weekly_analytics.md ``` ### Performance Investigation Analyze why quality might be declining or improving: ```bash /learning-analytics # Review Learning Velocity and Learning Patterns sections ``` ### Skill Selection Validation Verify which skills and combinations work best: ```bash /learning-analytics # Review Top Performing Skills and Skill Synergies sections ``` ## Interpretation Guide ### Quality Scores - **90-100**: Excellent - Optimal performance - **80-89**: Good - Meeting standards - **70-79**: Acceptable - Some improvement needed - **<70**: Needs attention - Review approach ### Learning Velocity - **Accelerating**: System is learning faster over time (optimal) - **Linear**: Steady improvement at constant rate (good) - **Decelerating**: Improvement slowing down (may need new approaches) ### Prediction Accuracy - **>85%**: High accuracy - Trust automated recommendations - **70-85%**: Moderate accuracy - System still learning - **<70%**: Low accuracy - Need more training data ### Skill Synergies - **Score >5**: Highly recommended combination - **Score 2-5**: Recommended combination - **Score <2**: Use with caution ## Frequency Recommendations - **After every 10 patterns**: Quick check of trends - **Weekly**: Full review of all sections - **Monthly**: Deep analysis with exported reports - **After major changes**: Verify impact on learning ## Notes - Analytics require at least 10 patterns for meaningful insights - Learning velocity requires 3+ weeks of data - Prediction accuracy improves with more training data - Cross-project learning activates automatically when enabled - All metrics update in real-time as new patterns are captured ---