compound

Extract project, methodology, and competency insights into structured sprint synthesis documents.

4|1|Updated Apr 11, 2026

Search Tags:#retrospective #agile #knowledge-management #sprint #capitalization #learning-notes #gse-one

Ready to run

npx skills add https://github.com/nicolasguelfi/gensem --skill compound-nicolasguelfi

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: compound
Source: https://github.com/nicolasguelfi/gensem/tree/main/gse-one/plugin/skills/compound
Command: npx skills add https://github.com/nicolasguelfi/gensem --skill compound-nicolasguelfi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Capitalize learnings across the sprint lifecycle by crystallizing patterns, feedback, and competency notes at sprint end to drive continuous improvement.

Core Features & Use Cases

End-of-sprint capitalization across three axes: Axe 1 (project learnings), Axe 2 (methodology feedback), and Axe 3 (competency notes).
Generate structured lessons learned, best practices, and technical debt items to docs/sprints/sprint-{ NN }/compound.md for traceability.
Proactively propose learning notes (LEARN items) and update the user profile with competency calibrations to sustain growth.

Quick Start

Trigger the /gse:compound command at sprint end to generate a capitalization report and persist results.

Frequently Asked Questions about compound

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

FAQPage Schema

How do I capitalize sprint learnings to drive continuous improvement?▼

To capitalize sprint learnings, trigger a capitalization command at sprint end to extract project, methodology, and competency insights. This generates a structured synthesis persisted to sprint artifacts and a compound.md file for traceability.

What is the best way to structure a post-sprint synthesis for an agile project?▼

A structured post-sprint synthesis should crystallize patterns across three axes: project learnings, methodology feedback, and competency notes. This approach generates lessons learned, best practices, and technical debt items for documentation.

How do I extract methodology feedback and competency notes during an end-of-sprint review?▼

Extracting methodology feedback and competency notes requires applying a multi-axe workflow during end-of-sprint reviews. This process proactively generates learning notes and updates user profiles with competency calibrations to sustain growth.

Where should I persist lessons learned and best practices after a sprint?▼

Persist lessons learned and best practices to docs/sprints/sprint-{ NN }/compound.md. This archival persistence ensures traceability and drives continuous improvement across the sprint lifecycle by compounding knowledge.

Can I generate technical debt items from my sprint retrospective?▼

Yes, generating technical debt items is a core feature of sprint capitalization. By crystallizing patterns and feedback at sprint end, the workflow outputs structured lessons learned and technical debt items directly to your sprint documentation.

Do I need any specific dependencies to run a multi-axe sprint capitalization workflow?▼

No specific dependencies are required to run this multi-axe sprint capitalization workflow. The process applies prerequisites, execution steps, and archival persistence directly to generate structured post-sprint syntheses without external tools.