Dani
054c0e56e9
Removed the deprecated 'model: sonnet' field from command frontmatter to fix compatibility issues with Claude Code. Commands will now inherit the model from the active conversation instead of using a hardcoded deprecated model identifier. Changes: - Removed 'model: sonnet' from 142 command files across all categories - Commands now use default model inheritance behavior - Preserved 'model: claude-sonnet-4-5-20250929' in gemini-review.md (valid model) - 67 commands without model field remain unchanged This resolves the "model: sonnet not found" error reported in GitHub issues and aligns with Claude Code's recommended practice of letting commands inherit the conversation model. Affected categories: - Database/Supabase commands (8 files) - Documentation commands (8 files) - Deployment commands (11 files) - Setup commands (14 files) - Performance commands (8 files) - Team commands (14 files) - Security commands (6 files) - NextJS/Vercel commands (10 files) - Sync commands (14 files) - And more across other categories 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Market Response Modeler
Model comprehensive market and customer responses with advanced behavioral prediction: $ARGUMENTS
Current Market Context
- Market definition: Based on $ARGUMENTS (target segments, geographic scope, competitive landscape)
- Response trigger: Product launch, pricing change, marketing campaign, or competitive response
- Available data: Customer behavior data, market research, and historical response patterns
- Success metrics: Key performance indicators for measuring response effectiveness
Task
Create comprehensive market response simulation with predictive analytics and optimization:
Market Trigger: Use $ARGUMENTS to model responses to product launches, pricing changes, marketing campaigns, or competitive actions
Response Framework:
- Market Segmentation - Comprehensive segment analysis with behavioral, demographic, and needs-based categorization
- Response Behavior Modeling - Customer journey mapping, response driver analysis, and intensity prediction
- Competitive Response Integration - Competitor reaction modeling and market dynamic effects
- Response Simulation Engine - Multi-scenario testing with timeline modeling and probability assessment
- Prediction Algorithms - Statistical modeling, machine learning, and expert system integration
- Response Optimization - Message, offering, channel, and timing optimization strategies
Advanced Analytics: Monte Carlo simulations, competitive game theory, behavioral economics integration, and real-time calibration.
Decision Support: Strategic recommendations with segment-specific tactics, risk mitigation, and success measurement frameworks.
Output: Complete market response prediction with segment analysis, optimization recommendations, competitive scenarios, and implementation guidelines for maximum market impact.