q-educator

Generate university lecture outlines, demo outlines, emails, and assignments through an interview-driven workflow.

Updated Mar 16, 2026
One-click install
npx skills add https://github.com/cgm-free/ai-education-platform --skill q-educator-cgm-free
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: q-educator
Source: https://github.com/cgm-free/ai-education-platform/tree/main/.agents/skills/q-educator
Command: npx skills add https://github.com/cgm-free/ai-education-platform --skill q-educator-cgm-free

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Instructors often struggle to translate abstract teaching goals into concrete, measurable course materials. Q-Educator provides an interview-driven, projects-first workflow that consistently yields lecture outlines, demo outlines, student emails, assignment prompts, and per-group feedback.

Core Features & Use Cases

  • Lecture outlines for weekly modules that map goals to content blocks and time allocations.
  • Demo outlines for live project walkthroughs that illustrate end-to-end workflows.
  • Follow-up emails to students that reinforce learning objectives and next steps.
  • Assignment prompts with scaffolded sections to guide student work and assessment criteria.
  • Per-group feedback documents that document group-level reasoning and improvement paths.
  • Iterative refinement steps governed by instructor review, ensuring alignment with course goals.

Quick Start

Initiate an instructor interview to clarify goals, then generate a Week 1 Lecture Outline, a Demo Outline, and a Follow-Up Email using the pipeline described.

Frequently Asked Questions about q-educator

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

FAQPage Schema
How do I create university course materials from abstract teaching goals?

Create university course materials through an interview-driven, projects-first workflow that translates abstract teaching goals into concrete lecture outlines, demo outlines, and student emails. The pipeline requires instructor input and iterative refinement to ensure alignment with course goals.

What is the best way to design scaffolded assignment prompts for university courses?

Design scaffolded assignment prompts using an instructional-design pipeline that generates sections to guide student work and assessment criteria. The workflow applies projects-first principles to ensure assignments map directly to measurable learning objectives.

How does an interview-driven course design workflow function?

An interview-driven course design workflow functions by initiating an instructor interview to clarify goals, then generating weekly lecture outlines, demo outlines, and follow-up emails. Iterative refinement steps governed by instructor review ensure explicit documentation and alignment.

Can I generate per-group feedback documents for project-based courses?

Generate per-group feedback documents through the projects-first workflow to document group-level reasoning and improvement paths. The pipeline produces feedback alongside lecture outlines and assignment prompts, ensuring comprehensive course material coverage.

Does instructional design for university courses require prior course planning experience?

Instructional design for university courses requires no explicit prior planning experience, but it demands instructor input during an initial interview to clarify goals. The workflow guides the creation of module materials through iterative refinement and explicit documentation.

When should I not use a projects-first approach for course design?

Avoid a projects-first approach when an instructor cannot commit to iterative refinement steps or providing domain-specific analogies. The workflow relies heavily on instructor review and structured pipeline documentation to yield measurable materials across weeks or modules.