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sprint-retro

Analyzes sprint data to compute metrics and generate an actionable improvement plan.

2|Updated Mar 19, 2026
Search Tags:#action plan#lessons learned#velocity#agile metrics#sprint retrospective#planning improvement#estimation calibration
One-click install
npx skills add https://github.com/EvanPluchart/kyomu --skill sprint-retro-evanpluchart
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sprint-retro
Source: https://github.com/EvanPluchart/kyomu/tree/main/.claude/skills/sprint-retro
Command: npx skills add https://github.com/EvanPluchart/kyomu --skill sprint-retro-evanpluchart

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps teams convert completed sprint work into measurable insights so they can improve estimation accuracy, identify recurring success and failure patterns, and produce a concrete action plan for the next sprint.

Core Features & Use Cases

  • Sprint metrics extraction: Reads sprint-status.yaml and computes velocity, total time, completion rate, blocking rate, and estimation precision by comparing estimated sizes versus real durations.
  • Pattern and learning aggregation: Analyzes lessons_learned to group repeated takeaways by theme (patterns, tools, architecture, process) and highlights both success patterns and failure patterns.
  • Calibration and action planning: Produces size calibration recommendations (S/M/L/XL) based on observed real durations and generates an actionable improvement plan saved as a retro-report.md.

Quick Start

Run the command /sprint-retro --sprint <chemin> to generate a sprint retro report, print it in the terminal, and save retro-report.md to the configured docs directory.

Frequently Asked Questions about sprint-retro

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate sprint velocity and estimation precision from completed work?▼

Calibrate S/M/L/XL story size thresholds by analyzing the real durations of completed sprint work recorded in sprint-status.yaml. The computed real-time data adjusts size categories to improve future estimation accuracy.

What's the best way to generate an actionable improvement plan from sprint retrospective lessons learned?▼

To run a sprint retrospective, execute the /sprint-retro command with the target sprint path. The tool reads sprint-status.yaml inputs, calculates performance metrics, prints the analysis in the terminal, and saves a retro-report.md under the configured docs directory.

Does sprint retrospective analysis require specific data formats for blocking rate calculation?▼

Yes, sprint retrospective analysis requires a sprint-status.yaml file containing stories with estimated sizes, real durations, declared difficulty, and lessons_learned. These structured inputs are necessary to accurately compute blocking rate and estimation precision.

Can I detect recurring failure patterns and success patterns from agile metrics?▼

Yes, you can detect recurring success and failure patterns by analyzing lessons_learned data grouped by themes like patterns, tools, architecture, and process. This aggregation highlights repeated takeaways to inform actionable planning improvements.

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