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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Team Workload Balancer
Analyze and optimize team workload distribution with intelligent assignment recommendations: $ARGUMENTS
Current Team Context
- Team size: !
git log --format='%ae' --since='1 month ago' | sort -u | wc -lactive team members - Active tasks: Linear MCP query for current sprint tasks and assignments
- Recent activity: !
git log --oneline --since='1 week ago' | wc -lcommits in last week - Capacity metrics: Analysis of team velocity and individual contribution patterns
Task
Execute comprehensive workload analysis with intelligent assignment optimization:
Analysis Type: Use $ARGUMENTS to focus on current workload assessment, skill matching, capacity planning, or assignment optimization
Workload Balancing Framework:
- Current Workload Assessment - Analyze task distribution, evaluate individual capacity, assess deadline pressure, identify overloaded team members
- Skill Matching Analysis - Map team member expertise, identify skill gaps, assess learning opportunities, optimize skill utilization
- Capacity Planning - Calculate available capacity, project future workload, plan skill development, optimize resource allocation
- Performance Integration - Analyze historical performance, identify productivity patterns, assess collaboration effectiveness, factor in availability constraints
- Assignment Optimization - Generate optimal task assignments, balance workload distribution, maximize skill utilization, minimize bottlenecks
- Risk Mitigation - Identify single points of failure, plan cross-training, assess knowledge distribution, ensure backup coverage
Advanced Features: Predictive workload modeling, skill gap analysis, burnout prevention, performance-based assignment, dynamic rebalancing recommendations.
Quality Metrics: Workload distribution equity, skill utilization efficiency, team satisfaction indicators, delivery predictability measures.
Output: Comprehensive workload analysis with optimized assignments, capacity recommendations, skill development plans, and team health insights.