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Initial commit: SuperClaude v4.0.0 configuration framework
- Core configuration files (CLAUDE.md, RULES.md, PERSONAS.md, MCP.md) - 17 slash commands for specialized workflows - 25 shared YAML resources for advanced configurations - Installation script for global deployment - 9 cognitive personas for specialized thinking modes - MCP integration patterns for intelligent tool usage - Token economy and ultracompressed mode support 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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.claude/commands/shared/performance-tracker.yml
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# Performance Tracking System
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## Legend
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| Symbol | Meaning | | Abbrev | Meaning |
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|--------|---------|---|--------|---------|
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| ⚡ | fast/optimized | | perf | performance |
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| 📊 | metrics/data | | exec | execution |
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| ⏱ | timing/duration | | tok | token |
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| 🔄 | continuous | | opt | optimization |
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## Metrics Collection
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```yaml
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Command_Performance:
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Timing_Metrics:
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Start_Time: "Record command initiation timestamp"
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End_Time: "Record command completion timestamp"
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Duration: "end_time - start_time"
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Phases: "breakdown by major operations"
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Token_Metrics:
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Input_Tokens: "Tokens in user command + context"
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Output_Tokens: "Tokens in response + tool calls"
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MCP_Tokens: "Tokens consumed by MCP servers"
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Efficiency_Ratio: "output_value / total_tokens"
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Operation_Metrics:
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Tools_Used: "List of tools called (Read, Edit, Bash, etc)"
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Files_Accessed: "Number of files read/written"
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MCP_Calls: "Which MCP servers used + frequency"
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Error_Count: "Number of errors encountered"
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Success_Metrics:
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Completion_Status: "success|partial|failure"
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User_Satisfaction: "interruptions, corrections, positive signals"
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Retry_Count: "Number of retry attempts needed"
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Quality_Score: "estimated output quality (1-10)"
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```
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## Performance Baselines
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```yaml
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Command_Benchmarks:
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Simple_Commands:
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analyze_file: "<5s, <500 tokens"
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read_file: "<2s, <200 tokens"
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edit_file: "<3s, <300 tokens"
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Medium_Commands:
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build_component: "<30s, <2000 tokens"
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test_execution: "<45s, <1500 tokens"
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security_scan: "<60s, <3000 tokens"
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Complex_Commands:
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full_analysis: "<120s, <5000 tokens"
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architecture_design: "<180s, <8000 tokens"
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comprehensive_scan: "<300s, <10000 tokens"
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MCP_Server_Performance:
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Context7: "<5s response, 100-2000 tokens typical"
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Sequential: "<30s analysis, 500-10000 tokens typical"
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Magic: "<10s generation, 500-2000 tokens typical"
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Puppeteer: "<15s operation, minimal tokens"
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```
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## Adaptive Optimization
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```yaml
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Real_Time_Optimization:
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Slow_Operations:
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Threshold: ">30s execution time"
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Actions:
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- Switch to faster tools (rg vs grep)
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- Reduce scope (specific files vs full scan)
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- Enable parallel processing
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- Suggest --uc mode for token efficiency
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High_Token_Usage:
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Threshold: ">70% context or >5K tokens"
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Actions:
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- Auto-suggest UltraCompressed mode
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- Cache repeated content
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- Use cross-references vs repetition
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- Summarize large outputs
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Error_Patterns:
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Repeated_Failures:
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Threshold: "3+ failures same operation"
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Actions:
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- Switch to alternative tool
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- Adjust approach/strategy
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- Request user guidance
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- Document known issue
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Success_Pattern_Learning:
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Track_Effective_Combinations:
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- Which persona + command + flags work best
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- Which MCP combinations are most efficient
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- Which file patterns lead to success
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- User preference patterns over time
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```
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## Monitoring Implementation
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```yaml
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Data_Collection:
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Lightweight_Tracking:
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- Minimal overhead (<1% performance impact)
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- Background collection (no user interruption)
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- Local storage only (privacy-preserving)
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- Configurable (can be disabled)
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Storage_Format:
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Location: ".claudedocs/metrics/performance-YYYY-MM-DD.jsonl"
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Format: "JSON Lines (one record per command)"
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Retention: "30 days rolling, aggregated monthly"
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Size_Limit: "10MB max per day"
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Data_Structure:
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timestamp: "ISO 8601 format"
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command: "Full command w/ flags"
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persona: "Active persona (if any)"
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duration_ms: "Execution time in milliseconds"
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tokens_input: "Input token count"
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tokens_output: "Output token count"
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tools_used: "Array of tool names"
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mcp_servers: "Array of MCP servers used"
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success: "boolean completion status"
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error_count: "Number of errors encountered"
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user_corrections: "Number of user interruptions/corrections"
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```
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## Reporting & Analysis
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```yaml
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Performance_Reports:
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Daily_Summary:
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Location: ".claudedocs/metrics/daily-summary-YYYY-MM-DD.md"
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Content:
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- Command execution statistics
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- Token efficiency metrics
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- Error frequency analysis
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- Optimization recommendations
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Weekly_Trends:
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Location: ".claudedocs/metrics/weekly-trends-YYYY-WW.md"
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Content:
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- Performance trend analysis
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- Usage pattern identification
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- Efficiency improvements over time
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- Bottleneck identification
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Optimization_Insights:
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Identify_Patterns:
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- Most efficient command combinations
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- Highest impact optimizations
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- User workflow improvements
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- System resource utilization
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Alerts:
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Performance_Degradation: "If avg response time >2x baseline"
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High_Error_Rate: "If error rate >10% over 24h"
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Token_Inefficiency: "If efficiency ratio drops >50%"
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```
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## Integration Points
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```yaml
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Command_Wrapper:
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Pre_Execution:
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- Record start timestamp
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- Capture input context size
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- Note active persona & flags
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During_Execution:
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- Track tool usage
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- Monitor MCP server calls
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- Count errors & retries
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Post_Execution:
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- Record completion time
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- Calculate token usage
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- Assess success metrics
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- Store performance record
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Auto_Optimization:
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Context_Size_Management:
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- Suggest /compact when context >70%
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- Auto-enable --uc for large responses
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- Cache expensive operations
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Tool_Selection:
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- Prefer faster tools for routine operations
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- Use parallel execution when possible
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- Skip redundant operations
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User_Experience:
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- Proactive performance feedback
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- Optimization suggestions
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- Alternative approach recommendations
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```
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## Usage Examples
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```yaml
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Basic_Monitoring:
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Automatic: "Built into all SuperClaude commands"
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Manual_Report: "/user:analyze --performance"
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Custom_Query: "Show metrics for last 7 days"
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Performance_Tuning:
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Identify_Bottlenecks: "Which commands are consistently slow?"
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Token_Optimization: "Which operations use most tokens?"
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Success_Patterns: "What combinations work best?"
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Continuous_Improvement:
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Weekly_Review: "Automated performance trend analysis"
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Optimization_Alerts: "Proactive performance degradation warnings"
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Usage_Insights: "Learn user patterns for better defaults"
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```
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---
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*Performance Tracker v1.0 - Intelligent monitoring & optimization for SuperClaude operations*
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