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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/loading-config.yml
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.claude/commands/shared/loading-config.yml
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# Loading Config for Token Optimization & Perf
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## Core Config (Always Load)
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```yaml
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Core:
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Always: [CLAUDE.md, RULES.md, PERSONAS.md, MCP.md]
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Priority: Critical behavioral rules, personas & MCP patterns
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Size: ~4600 tokens
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Reason: Essential for all Claude Code behavior, personas globally available
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Global Availability:
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PERSONAS.md: All 9 cognitive archetypes available via /persona:
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MCP.md: All MCP patterns available automatically
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Commands:
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Trigger: /user:
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Path: .claude/commands/
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Size: ~50 tokens per command
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Cache: Most recent 5 commands
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Index: command names & risk levels only
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SharedResources:
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LoadWith: Associated commands
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Path: .claude/commands/shared/
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Size: ~150 tokens per YAML
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Examples:
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- cleanup-patterns.yml→loads w/ /user:cleanup
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- git-workflow.yml→loads w/ git ops
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- planning-mode.yml→loads w/ risky commands
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```
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## Advanced Loading Optimization
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```yaml
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Smart Loading Strategies:
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Predictive: Anticipate likely-needed resources based on command patterns
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Contextual: Load resources based on project type and user behavior
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Lazy: Defer loading non-critical resources until explicitly needed
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Incremental: Load minimal first, expand as complexity increases
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Intelligent Caching:
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Command Frequency: Cache most-used commands permanently
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Workflow Patterns: Preload resources for common command sequences
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User Preferences: Remember and preload user's preferred tools
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Session Context: Keep relevant context across related operations
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Token Efficiency:
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Base load: 4600 tokens (CLAUDE.md + RULES.md + PERSONAS.md + MCP.md)
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Optimized commands: 4650-4700 tokens (~50 tokens per command)
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Smart shared resources: Load only when needed, avg 150-300 tokens
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Performance gain: ~20-30% reduction through intelligent loading
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Trade-off: Higher base load for consistent global functionality
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Context Compression:
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Auto UltraCompressed: Enable when context approaches limits
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Selective Detail: Keep summaries, load detail on demand
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Result Caching: Store and reuse expensive analysis results
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Pattern Recognition: Learn and optimize based on usage patterns
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```
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## Performance Monitoring Integration
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```yaml
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Loading Metrics:
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Time to Load: Track component loading speed
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Cache Hit Rate: Measure effectiveness of caching strategies
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Memory Usage: Monitor total context size and optimization opportunities
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User Satisfaction: Track command completion success rates
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Adaptive Optimization:
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Slow Loading: Automatically switch to lighter alternatives
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High Memory: Trigger context compression and cleanup
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Cache Misses: Adjust caching strategy based on usage patterns
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Performance Degradation: Fall back to minimal loading mode
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```
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