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bce31d52a8
- 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>
86 lines
3.0 KiB
YAML
86 lines
3.0 KiB
YAML
# Perf Self-Monitoring & Optimization
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## Tracking Metrics
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```yaml
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Op Duration: Track time per command | Average vs current | Trend analysis
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Token Consumption: Monitor usage per op | Compare→baselines | Efficiency ratios
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Success Rates: Command completion % | Error frequency | Retry patterns
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User Satisfaction: Interruption frequency | Correction patterns | Positive signals
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```
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## Perf Thresholds
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```yaml
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Time Limits:
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>30s ops→Consider alternatives | Switch→faster method
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>60s→Force timeout | Explain delay | Offer cancellation
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Token Limits:
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>2K tokens single op→Simplify approach | Break→smaller parts
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>5K session→Suggest /compact | Warn about context size
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Error Patterns:
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3+ retries same op→Switch strategy | Try different tool
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Repeated failures→Escalate→manual approach | Ask→guidance
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```
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## Adaptive Strategies
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```yaml
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When Slow:
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File operations → Use faster tools (rg vs grep)
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Large codebases → Focus on specific areas
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Complex analysis → Progressive refinement
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When High Token Usage:
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Verbose output → Switch to concise mode
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Repeated content → Use references instead
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Large responses → Summarize key points
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When Errors Occur:
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Tool failures → Try alternative tools
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Permission issues → Suggest fixes
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Missing dependencies → Guide installation
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```
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## Advanced Performance Optimization
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```yaml
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Token Usage Optimization:
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Smart Context: Keep only essential information between commands
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Compression: Auto-enable --uc mode when context >70%
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Caching: Store and reuse expensive analysis results
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Selective MCP: Use most efficient MCP tool for each task
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Command Optimization:
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Parallel Execution: Run independent operations concurrently
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Early Returns: Complete when objectives achieved
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Progressive Refinement: Start broad, narrow focus as needed
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Smart Defaults: Reduce configuration overhead
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Workflow Acceleration:
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Pattern Recognition: Learn from successful command sequences
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Predictive Context: Preload likely-needed resources
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Skip Redundant: Avoid re-analysis of unchanged files
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Chain Optimization: Optimize common workflow patterns
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```
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## Performance Reporting
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```yaml
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Real-Time Feedback:
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Transparency: "Operation taking longer than expected, switching to faster method"
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Updates: "Optimizing approach to reduce token usage"
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Alternatives: "Primary method failed, trying backup approach"
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Success: "Completed efficiently using optimized strategy"
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Metrics Collection:
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Location: .claudedocs/metrics/performance-<date>.md
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Frequency: Daily aggregation + real-time monitoring
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Content: Operation times | Token usage | Success rates | Error patterns | Optimization wins
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Format: Markdown with tables and charts
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Auto-create: mkdir -p .claudedocs/metrics/
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Performance Insights:
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Bottleneck Identification: Which operations consume most resources
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Efficiency Trends: Performance improvement over time
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User Patterns: Most effective workflows and flag combinations
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Optimization Recommendations: Specific suggestions for improvement
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``` |