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Retrospective Analyzer

Commands team 200 Scanned by NVIDIA SkillSpector

Analyze team retrospectives with quantitative metrics and actionable insights generation

Install Command
npx claude-code-templates@latest --command team/retrospective-analyzer
View on GitHub
claude-code — retrospective-analyzer

Scanned by NVIDIA SkillSpector

Automated static analysis (no LLM) · v2.12.0 · 2026-10-23

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Content

Retrospective Analyzer

Analyze team retrospectives with comprehensive metrics and actionable improvement insights: $ARGUMENTS

Current Retrospective Context

  • Sprint period: !git log --oneline --since='2 weeks ago' | wc -l commits in recent sprint
  • Team activity: Analysis of recent collaboration patterns and productivity metrics
  • Linear sprint: Current sprint data and completion metrics from Linear MCP
  • Previous retrospectives: Historical retrospective data and improvement tracking

Task

Execute comprehensive retrospective analysis with quantitative insights and improvement recommendations:

Analysis Focus: Use $ARGUMENTS to specify sprint identifier, quantitative metrics, insight generation, action item tracking, or trend analysis

Retrospective Analysis Framework:

  1. Sprint Performance Analysis - Analyze velocity trends, completion rates, cycle time metrics, quality indicators
  2. Team Collaboration Assessment - Evaluate communication patterns, code review effectiveness, knowledge sharing, pair programming impact
  3. Process Effectiveness - Assess meeting efficiency, planning accuracy, impediment resolution, workflow optimization
  4. Quality Metrics - Analyze bug rates, technical debt accumulation, code review quality, testing effectiveness
  5. Individual Contribution - Evaluate workload distribution, skill development, mentorship activities, cross-training progress
  6. Actionable Insights Generation - Identify improvement opportunities, prioritize action items, track progress, measure impact

Advanced Features: Trend analysis across multiple sprints, predictive performance modeling, team satisfaction correlation, continuous improvement tracking.

Insight Quality: Data-driven recommendations, quantified improvement potential, implementation feasibility, success measurement criteria.

Output: Comprehensive retrospective analysis with quantitative metrics, actionable insights, prioritized improvements, and progress tracking framework.

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