des-retrospective

Generate evidence-grounded retrospective reports for DES data engineering implementation cycles.

2|Updated May 20, 2026
One-click install
npx skills add https://github.com/DKSang/DES-SKILL --skill des-retrospective
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: des-retrospective
Source: https://github.com/DKSang/DES-SKILL/tree/main/skills-support/des-retrospective
Command: npx skills add https://github.com/DKSang/DES-SKILL --skill des-retrospective

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

DES retrospective support helps teams and agents capture what happened in a data engineering implementation cycle, trace friction back to root causes, and produce a concrete improvement loop instead of unstructured post-mortems.

Core Features & Use Cases

  • Evidence-grounded retrospectives: Compares planned vs completed work using sprint plan, story catalog, workflow status, and (when available) code review and release readiness artifacts, while explicitly marking evidence gaps.
  • Actionable learning and iteration: Extracts what went well, what did not go well, root causes, technical/quality/governance/CI-CD lessons, and produces action items plus next-sprint recommendations.
  • Workflow-aware outputs: Updates workflow status and provides a next recommended support skill (e.g., correct-course) aligned with the retrospective outcome.

Quick Start

Use the des-retrospective skill after sprint closeout to generate _des-output/implementation-artifacts/retrospective-report.md from the available sprint-plan and story-catalog evidence.

Frequently Asked Questions about des-retrospective

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

FAQPage Schema
How do I generate an evidence-grounded retrospective report for a data engineering sprint?

To generate an evidence-grounded retrospective report, compare planned versus completed work using sprint plans and story catalogs. The system extracts blockers, root causes, and lessons learned, explicitly marking any evidence gaps before producing the final report.

What is the best way to analyze sprint blockers and CI/CD lessons in a data engineering workflow?

Analyzing sprint blockers and CI/CD lessons involves tracing friction back to root causes during implementation cycle reviews. The process evaluates technical, quality, and governance outcomes to produce actionable improvement items rather than unstructured post-mortems.

How do I run a retrospective when upstream implementation artifacts are incomplete?

When upstream implementation artifacts are incomplete, the retrospective process explicitly marks evidence gaps rather than fabricating results. It proceeds by comparing available sprint plan and workflow status data to generate a report with clearly documented missing inputs.

Can I use sprint retrospective outputs to update workflow status and recommend next steps?

Yes, sprint retrospective outputs directly update workflow status files with explicit next-step decisions. The process recommends a subsequent support skill, such as correct-course, aligned with the retrospective outcome to drive continuous workflow iteration.

When do I need a retrospective report for release readiness and handoff reviews?

A retrospective report is needed for release readiness, demo, or handoff reviews when you must evaluate implementation cycle outcomes against the original plan. It captures technical and governance lessons to ensure smoother future deployments.

Does the des-retrospective workflow support artifact quality and governance analysis?

Yes, the retrospective workflow supports artifact quality and governance analysis by evaluating completed work against expected standards. It extracts specific governance lessons and quality issues to form concrete action items for the next sprint.