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>
2.4 KiB
Team Velocity Tracker
Track team velocity patterns with predictive forecasting and performance optimization: $ARGUMENTS
Current Velocity Context
- Sprint velocity: !
git log --oneline --since='2 weeks ago' | wc -lcommits per current sprint - Team consistency: Analysis of velocity stability across recent sprints
- Linear tracking: Sprint point completion rates and story delivery metrics
- Capacity factors: Team size changes, availability, and skill development impact
Task
Execute comprehensive velocity tracking with predictive analytics and optimization recommendations:
Analysis Period: Use $ARGUMENTS to focus on sprint velocity, monthly trends, quarterly patterns, or comprehensive trend analysis
Velocity Tracking Framework:
- Historical Velocity Analysis - Extract sprint completion data, analyze story point delivery, calculate team throughput, identify performance patterns
- Consistency Assessment - Measure velocity stability, identify variance patterns, assess predictability factors, evaluate planning accuracy
- Capacity Correlation - Analyze team size impact, assess skill level effects, evaluate availability constraints, measure external factor influence
- Predictive Forecasting - Generate velocity projections, predict sprint outcomes, estimate delivery timelines, calculate confidence intervals
- Performance Optimization - Identify improvement opportunities, recommend capacity adjustments, suggest process enhancements, optimize team composition
- Quality Integration - Correlate velocity with quality metrics, assess technical debt impact, evaluate sustainable pace, measure team satisfaction
Advanced Features: Monte Carlo forecasting, velocity trend decomposition, capacity planning optimization, performance anomaly detection, sustainable pace analysis.
Predictive Analytics: Sprint outcome predictions, delivery timeline forecasting, capacity requirement planning, performance trend analysis.
Output: Comprehensive velocity analysis with predictive forecasts, optimization recommendations, capacity planning insights, and sustainable performance strategies.