recent - Command History & Pattern Analysis

Purpose

Intelligent command history system that shows your recently used hAIveMind commands with success rates, execution times, and pattern analysis to help optimize your workflow and identify improvement opportunities.

When to Use

Performance Analysis: Review command success rates and execution times
Workflow Optimization: Identify patterns in your command usage for efficiency improvements
Troubleshooting: Analyze recent failures to identify recurring issues
Learning: Understand your usage patterns and discover optimization opportunities
Audit Trail: Review recent actions for compliance or debugging purposes
Pattern Recognition: Discover successful command sequences for future use

Syntax

recent [limit]

Parameters

limit (optional): Number of recent commands to display (default: 10, max: 50)
- Examples: recent 5, recent 20, recent 50

Intelligent Analysis Features

Usage Pattern Recognition

Command Sequences: Identifies common command patterns and their success rates
Timing Analysis: Analyzes time between commands to identify workflow efficiency
Success Correlation: Shows which command combinations lead to best outcomes
Context Awareness: Correlates command usage with project types and situations
Trend Analysis: Identifies changes in usage patterns over time

Performance Insights

Execution Time Tracking: Shows how long each command took to complete
Success Rate Analysis: Tracks which commands succeed most often
Error Pattern Detection: Identifies recurring failure patterns
Efficiency Metrics: Calculates workflow efficiency and suggests improvements
Comparative Analysis: Compares your patterns with collective best practices

Real-World Examples

Basic Recent Command History

recent

Result: Last 10 commands with timestamps, success status, execution times, and context

Extended History Analysis

recent 25

Result: Last 25 commands with detailed pattern analysis, success trends, and optimization suggestions

Quick Recent Check

recent 5

Result: Last 5 commands with focus on immediate recent activity and quick insights

Expected Output

Standard Recent Commands View

⏱️ Recent Command History - 2025-01-24 14:30:00

📊 Usage Summary (Last 10 commands):
   ↳ Total Commands: 10
   ↳ Success Rate: 90% (9 successful, 1 failed)
   ↳ Average Execution Time: 1.8 seconds
   ↳ Most Used: hv-status (3x), remember (2x), hv-query (2x)

🔄 Recent Commands:

1. ✓ hv-status --detailed                    14:28:45  1.2s  general
   ↳ Success: Checked collective health, found 2 agents with high response times
   ↳ Context: Routine health monitoring
   ↳ Follow-up: Led to investigation of performance issues

2. ✓ hv-broadcast "Database optimization completed" infrastructure info  14:25:30  0.8s  infrastructure
   ↳ Success: Notified 12 agents about database improvements
   ↳ Context: Completing database optimization project
   ↳ Impact: Team aware of performance improvements

3. ✓ remember "Database query optimization reduced response time by 60%" infrastructure  14:23:15  0.5s  documentation
   ↳ Success: Documented optimization results for future reference
   ↳ Context: Preserving successful optimization techniques
   ↳ Tags: database, optimization, performance

4. ✓ hv-delegate "Monitor database performance metrics" monitoring  14:20:45  2.1s  task_assignment
   ↳ Success: Assigned monitoring task to monitoring specialists
   ↳ Context: Ensuring optimization results are tracked
   ↳ Assigned to: monitoring-agent, grafana-agent

5. ✓ hv-query "database performance optimization techniques"  14:18:30  3.2s  research
   ↳ Success: Found 8 relevant memories with optimization strategies
   ↳ Context: Researching before implementing database changes
   ↳ Results: Query indexing, connection pooling, cache strategies

6. ✗ hv-sync --force                         14:15:20  timeout  system_maintenance
   ↳ Failed: Timeout during configuration synchronization
   ↳ Context: Attempting to update agent configurations
   ↳ Error: Network connectivity issues with 3 agents
   ↳ Resolution: Retry succeeded after network stabilized

7. ✓ recall "database issues last 7 days" incidents  14:12:10  1.9s  investigation
   ↳ Success: Retrieved 4 recent database-related incidents
   ↳ Context: Understanding recent database problems before optimization
   ↳ Findings: Connection pool issues, slow query patterns

8. ✓ hv-status                               14:10:05  0.9s  general
   ↳ Success: Quick health check before starting database work
   ↳ Context: Verifying system stability before changes
   ↳ Status: All systems operational, ready for optimization

9. ✓ help hv-delegate                        14:08:30  0.3s  learning
   ↳ Success: Reviewed delegation syntax and best practices
   ↳ Context: Learning proper task delegation techniques
   ↳ Outcome: Better understanding of specialist assignment

10. ✓ remember "Starting database optimization project" infrastructure  14:05:15  0.4s  documentation
    ↳ Success: Documented project initiation for tracking
    ↳ Context: Beginning systematic database performance improvement
    ↳ Project: Database optimization initiative

📈 Pattern Analysis:

🎯 Successful Command Sequences (Last 24 hours):
   1. help → hv-query → hv-delegate → hv-broadcast (Success Rate: 100%, Used 3 times)
      ↳ Pattern: Learn → Research → Assign → Communicate
      ↳ Average Duration: 8.2 minutes
      ↳ Effectiveness: High - leads to well-informed actions

   2. hv-status → recall → remember (Success Rate: 95%, Used 4 times)
      ↳ Pattern: Check → Research → Document
      ↳ Average Duration: 4.1 minutes
      ↳ Effectiveness: High - good for investigation workflows

   3. remember → hv-broadcast → hv-delegate (Success Rate: 90%, Used 2 times)
      ↳ Pattern: Document → Communicate → Assign
      ↳ Average Duration: 3.8 minutes
      ↳ Effectiveness: Good - effective for sharing and follow-up

⏱️ Timing Patterns:
   ↳ Average time between commands: 3.2 minutes
   ↳ Fastest sequence: help → hv-query (30 seconds)
   ↳ Longest gap: 15 minutes (between investigation and action)
   ↳ Most efficient hour: 14:00-15:00 (current session)

🚀 Performance Insights:
   ↳ Commands with <1s execution time: 60% (very efficient)
   ↳ Commands with >3s execution time: 20% (investigate optimization)
   ↳ Network-dependent commands: 30% (consider local caching)
   ↳ Documentation commands: 30% (good knowledge preservation)

💡 Optimization Recommendations:

1. 🎯 Workflow Efficiency
   ↳ Your "help → research → act" pattern is highly effective (100% success)
   ↳ Consider standardizing this approach for complex tasks
   ↳ Time savings: ~15% by following proven patterns

2. ⚡ Command Performance
   ↳ hv-query commands taking >3s - consider more specific search terms
   ↳ hv-sync timeout suggests network optimization needed
   ↳ Batch similar commands to reduce context switching

3. 📚 Documentation Habits
   ↳ Good documentation frequency (30% of commands)
   ↳ Consider adding more context tags to remember commands
   ↳ Document failed attempts for collective learning

4. 🔄 Pattern Optimization
   ↳ Your command sequences show good planning and follow-through
   ↳ Consider using workflows command for complex multi-step procedures
   ↳ Share successful patterns with team via hv-broadcast

📊 Comparative Analysis:
   ↳ Your success rate (90%) is above collective average (87%)
   ↳ Your documentation rate (30%) is excellent (collective: 18%)
   ↳ Your command diversity shows good tool utilization
   ↳ Time between commands suggests thoughtful execution

🎯 Recommended Next Steps:
   1. Continue current documentation practices - they're excellent
   2. Investigate hv-sync timeout issues for better reliability
   3. Consider using workflows for your successful command patterns
   4. Share your effective patterns with team via hv-broadcast

Extended History with Deep Analysis

⏱️ Extended Command History Analysis - Last 25 Commands

📊 Comprehensive Usage Statistics:
   ↳ Total Commands: 25 (last 4 hours)
   ↳ Success Rate: 88% (22 successful, 3 failed)
   ↳ Average Execution Time: 2.1 seconds
   ↳ Command Diversity: 7 different commands used
   ↳ Most Active Period: 14:00-15:00 (12 commands)

🔍 Command Frequency Analysis:
   1. hv-status: 8 uses (32%) - Avg: 1.1s, Success: 100%
   2. remember: 5 uses (20%) - Avg: 0.6s, Success: 100%
   3. hv-query: 4 uses (16%) - Avg: 2.8s, Success: 75%
   4. hv-broadcast: 3 uses (12%) - Avg: 0.9s, Success: 100%
   5. hv-delegate: 2 uses (8%) - Avg: 2.3s, Success: 100%
   6. recall: 2 uses (8%) - Avg: 1.7s, Success: 100%
   7. hv-sync: 1 use (4%) - Avg: timeout, Success: 0%

📈 Trend Analysis (4-hour window):
   ↳ Command frequency increasing (2 → 5 → 8 → 10 per hour)
   ↳ Success rate stable around 88-92%
   ↳ Documentation rate increasing (good trend)
   ↳ Research-heavy period (multiple hv-query commands)

🎯 Advanced Pattern Recognition:

Workflow Pattern: "Database Optimization Project"
   Timeline: 14:05 - 14:30 (25 minutes)
   Commands: remember → help → hv-query → recall → hv-delegate → remember → hv-broadcast → hv-status
   Success Rate: 87.5% (7/8 successful)
   Outcome: Successful database optimization with team coordination
   
   Pattern Breakdown:
   1. Project initiation (remember) ✓
   2. Learning phase (help) ✓
   3. Research phase (hv-query) ✓
   4. Historical analysis (recall) ✓
   5. Task assignment (hv-delegate) ✓
   6. Documentation (remember) ✓
   7. Team communication (hv-broadcast) ✓
   8. Verification (hv-status) ✓

Success Factors:
   ✓ Systematic approach with clear phases
   ✓ Good balance of research and action
   ✓ Proper documentation at key points
   ✓ Team communication and coordination
   ✓ Verification of outcomes

🚨 Failure Analysis:

Failed Command: hv-sync --force (14:15:20)
   ↳ Error Type: Network timeout
   ↳ Context: System maintenance during active work
   ↳ Impact: Delayed workflow by 5 minutes
   ↳ Resolution: Retry after network stabilization
   ↳ Prevention: Check network status before sync operations

Failed Commands Pattern:
   ↳ 3 failures out of 25 commands (12% failure rate)
   ↳ All failures were network-related (hv-sync, hv-query timeouts)
   ↳ Failures clustered around 14:15-14:20 (network issue period)
   ↳ No command logic or parameter errors

🎯 Optimization Opportunities:

1. Network Reliability (Priority: High)
   ↳ 100% of failures were network-related
   ↳ Consider network diagnostics before critical operations
   ↳ Implement retry logic for network-dependent commands
   ↳ Monitor network status: hv-status --network

2. Query Optimization (Priority: Medium)
   ↳ hv-query commands averaging 2.8s (above optimal)
   ↳ Use more specific search terms to reduce search time
   ↳ Consider caching frequently accessed information
   ↳ Break complex queries into smaller, focused searches

3. Workflow Standardization (Priority: Low)
   ↳ Your successful patterns could be formalized into workflows
   ↳ Database optimization pattern highly successful (87.5%)
   ↳ Consider creating custom workflow templates
   ↳ Share successful patterns with collective via documentation

📊 Performance Benchmarking:

Your Performance vs. Collective Averages:
   ↳ Success Rate: 88% (You) vs 87% (Collective) - Above Average ✓
   ↳ Execution Time: 2.1s (You) vs 1.8s (Collective) - Slightly Slower
   ↳ Documentation Rate: 20% (You) vs 18% (Collective) - Above Average ✓
   ↳ Command Diversity: 7 types (You) vs 5.2 (Collective) - Above Average ✓

Strengths:
   ✓ Excellent documentation habits
   ✓ Good command diversity and tool utilization
   ✓ Systematic approach to complex tasks
   ✓ Strong success rate despite network challenges

Improvement Areas:
   ↳ Network connectivity optimization
   ↳ Query efficiency improvement
   ↳ Command execution speed optimization

Advanced Analysis Features

Pattern Learning and Prediction

Success Prediction: Predicts likelihood of command success based on context and history
Workflow Recognition: Automatically identifies recurring workflow patterns
Optimization Suggestions: Recommends command sequence improvements
Timing Optimization: Suggests optimal timing for command execution
Context Correlation: Links command success to environmental factors

Collective Intelligence Integration

Benchmark Comparison: Compares your patterns with collective best practices
Success Rate Analysis: Shows how your success rates compare to other agents
Pattern Sharing: Identifies successful patterns worth sharing with collective
Learning Opportunities: Suggests areas for improvement based on collective data
Best Practice Adoption: Recommends proven patterns from high-performing agents

Performance Considerations

History Storage: Command history stored locally and in collective memory
Analysis Speed: Pattern analysis completed in <500ms for typical history sizes
Memory Usage: Optimized storage of command metadata and outcomes
Privacy: Personal command history separate from collective analytics
Retention: Command history retained for 30 days, patterns preserved longer

Related Commands

For workflow optimization: Use workflows to see formalized patterns
For command help: Use help <command> to understand failed commands
For examples: Use examples to see successful usage patterns
For suggestions: Use suggest to get recommendations based on recent patterns
For analytics: Use help analytics to see broader usage statistics

Troubleshooting Recent Command Analysis

Missing Command History

❓ No recent commands shown or incomplete history
💡 Possible Causes:
   1. New installation - history builds over time
   2. Command tracking not enabled
   3. History storage issues
   4. Use commands to build history for analysis

Inaccurate Success Rates

⚠️ Success rates don't match actual experience
💡 Troubleshooting:
   1. Success tracking depends on command completion detection
   2. Network timeouts may be misclassified
   3. Manual verification of recent command outcomes
   4. Report discrepancies for system improvement

Performance Analysis Issues

🐌 Pattern analysis taking too long or failing
💡 Resolution Steps:
   1. Reduce history limit for faster analysis
   2. Check system resources during analysis
   3. Clear analysis cache if available
   4. Report performance issues for optimization

Best Practices for Command History Analysis

Regular Review: Check recent commands daily to identify patterns and issues
Learn from Failures: Analyze failed commands to prevent future issues
Optimize Patterns: Use successful patterns as templates for future work
Share Insights: Document and share successful patterns with team
Track Improvements: Monitor how changes affect success rates and efficiency
Use for Planning: Let recent patterns inform future workflow planning

Continuous Improvement: The recent command analysis system learns from your usage patterns to provide increasingly accurate insights and optimization recommendations, helping you become more effective over time.

/recent Command