reflect

Analyze completed SIC runs to evaluate process performance and suggest improvements.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/karaposu/homegrown --skill reflect-karaposu
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: reflect
Source: https://github.com/karaposu/homegrown/tree/main/homegrown/reflect
Command: npx skills add https://github.com/karaposu/homegrown --skill reflect-karaposu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

It enables teams to evaluate their SIC (Sensemaking, Innovation, Critique) process quality by examining how well each phase performed and identifying areas for improvement.

Core Features & Use Cases

  • Process Evaluation: Analyzes the thoroughness and accuracy of each SIC step after completion.
  • Learning and Improvement: Produces insights, proposed memory improvements, and questions to refine future runs.
  • Use Case: After a complex problem-solving session, review the process to identify missed perspectives or potential process enhancements.

Quick Start

Read the outputs of the SIC run, then feed the folder containing sensemaking, innovation, critique, and reflection files into the reflection skill to generate an improvement report.

Frequently Asked Questions about reflect

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

FAQPage Schema
How do I evaluate process quality after a complex problem-solving session?

Improve future iterations by performing a second-order evaluation of your reasoning steps, assessing quality and coverage gaps to produce insights and proposed memory improvements that refine subsequent runs.

What is second-order evaluation in process improvement?

By evaluating the quality and coverage of reasoning steps, it identifies potential gaps in the thinking process and produces targeted insights and memory improvements to facilitate learning for future iterations.

How do I analyze completed runs to identify missed perspectives?

Generate an improvement report by feeding a folder containing sensemaking, innovation, critique, and reflection files into the analyzer to assess process performance and identify missed perspectives.

When do I need to review process performance for machine learning workflows?

You need process review after a complex problem-solving session to evaluate how well each phase performed, identify areas for improvement, and produce insights that refine future iterations.

Does the reflection process require specific input file formats?

Yes, it requires a folder containing sensemaking, innovation, critique, and reflection files from a completed run to accurately assess process performance and generate targeted improvement suggestions.