How does the Monte Carlo simulation improve sprint planning?

It runs thousands of iterations based on historical velocity to provide a range of probable outcomes rather than a single point estimate, allowing for more realistic commitments.

What is the minimum number of sprints needed for analysis?

While it can run on 3 sprints, 6 or more sprints are recommended for statistically significant Monte Carlo forecasting and trend detection.

What data format does this skill require?

The skill processes JSON data exported from project management tools like Jira, following a specific schema included in the skill's assets folder.

Can this skill help identify why a team is missing sprint goals?

Yes, the Sprint Health Scorer analyzes dimensions like scope stability and blocker resolution to pinpoint specific areas affecting reliability.

Scrum Master Expert

Name: Scrum Master Expert
Author: micsapp

bymicsapp

0•

Herramientas de Colaboración

Optimizes agile team performance through data-driven sprint analysis, probabilistic forecasting, and automated health scoring.

The Scrum Master Expert skill empowers Claude to act as a high-level agile coach by analyzing sprint data using specialized Python scripts. It facilitates precise sprint planning through Monte Carlo simulations, evaluates team health across six weighted dimensions, and tracks retrospective action items to ensure continuous improvement. By processing JSON exports from tools like Jira, it provides actionable insights into velocity trends, blocker resolution, and team maturity, making it an essential companion for engineering managers and Scrum Masters seeking objective, metrics-based guidance.

Características Principales

01Multi-dimensional sprint health scoring based on commitment and stability

020 GitHub stars

03Automated retrospective analysis for theme and action-item tracking

04Probabilistic planning guidance to calibrate sprint commitments

05Monte Carlo velocity forecasting with 50/70/85/95% confidence intervals

06Team maturity assessment using the forming-storming-norming-performing model

Casos de Uso

01Automating the preparation of retrospective insights and data-driven team improvement plans

02Predicting project delivery timelines using historical sprint data and probabilistic modeling

03Diagnosing team performance bottlenecks by analyzing scope stability and blocker resolution times

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add micsapp/micstec-skills scrum-master

For use in Claude.ai and ChatGPT

Características Principales

01Multi-dimensional sprint health scoring based on commitment and stability

020 GitHub stars

03Automated retrospective analysis for theme and action-item tracking

04Probabilistic planning guidance to calibrate sprint commitments

05Monte Carlo velocity forecasting with 50/70/85/95% confidence intervals

06Team maturity assessment using the forming-storming-norming-performing model

Casos de Uso

01Automating the preparation of retrospective insights and data-driven team improvement plans

02Predicting project delivery timelines using historical sprint data and probabilistic modeling

03Diagnosing team performance bottlenecks by analyzing scope stability and blocker resolution times