Analyze development iteration metrics and generate retrospective reports from historical project data.
npx skills add https://github.com/arch-team/devpace --skill pace-analyst
Please help me install this Agent Skill. Skill: pace-analyst Source: https://github.com/arch-team/devpace/tree/main/skills/pace-retro Command: npx skills add https://github.com/arch-team/devpace --skill pace-analyst
This Skill provides in-depth analysis of development iterations, identifies bottlenecks, and offers data-driven recommendations to improve quality, efficiency, and predictability.
/pace-retro to get a full report on what went well, what didn't, and actionable advice for the next cycle. Use /pace-retro compare to see how this iteration stacks up against the last.Run /pace-retro to generate a full retrospective report for the current iteration.
High-intent search queries and answers about installing and using this skill.
To generate a retrospective report, run the `/pace-retro` command. This analyzes your iteration metrics to review delivery performance, assess quality, and provide actionable insights for process improvement.
Yes, you can compare delivery performance metrics by running `/pace-retro compare`. This tracks key performance indicators over multiple iterations to identify long-term trends and stability.
Predictive forecasting analyzes historical project data to calculate delivery probability. It evaluates past iteration logs and dashboard metrics to flag potential risks and forecast outcomes for upcoming cycles.
Iteration trend analysis requires access to your project backlog, iteration logs, and dashboard metrics. Providing this comprehensive historical data ensures accurate quality assessment and reliable performance forecasting.
The best way to identify bottlenecks is analyzing historical iteration logs with retrospective reporting tools. This evaluates delivery and quality metrics to pinpoint inefficiencies and offer data-driven recommendations.
Iteration analysis works for any project scale where historical backlog and dashboard metrics are available. Comprehensive evaluation requires consistent iteration logs to generate accurate trend analysis and forecasting.
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