# AI Socratic Dialogue Designer

Design a multi-round questioning sequence for interrogating AI chatbot answers...

- Repository: https://github.com/GarethManning/education-agent-skills (939 stars)
- Category: Design
- License: see repository
- Last updated: 2026-10-22
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add GarethManning/education-agent-skills --skill ai-socratic-dialogue-designer -g -a claude-code -y`
Codex: `npx skills add GarethManning/education-agent-skills --skill ai-socratic-dialogue-designer -g -a codex -y`
Cursor: `npx skills add GarethManning/education-agent-skills --skill ai-socratic-dialogue-designer -g -a cursor -y`
Gemini CLI: `npx skills add GarethManning/education-agent-skills --skill ai-socratic-dialogue-designer -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add GarethManning/education-agent-skills`

## Description

Design a multi-round questioning sequence for interrogating AI chatbot answers, tracking how responses shift and distinguishing genuine updates from sycophantic capitulation. Use when teaching students to probe AI critically.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# AI Socratic Dialogue Designer

## What This Skill Does

Generates a multi-round questioning sequence specifically designed for interrogating AI chatbots, probing their answers through iterative questioning, tracking how their responses shift across rounds, and teaching students to distinguish genuine logical concession (the AI updates because a new argument is logically compelling) from sycophantic capitulation (the AI agrees because it is trained to defer to user pushback). This addresses a fundamental asymmetry between AI Socratic dialogue and human Socratic dialogue: AI systems are trained to be helpful and agreeable, which means they will often revise their answers in response to user pushback regardless of whether the pushback is logically valid. A student who pushes back on an AI answer and receives an updated, more agreeable response may conclude that persistence equals correctness, a false inference with significant implications for how they evaluate evidence. The pedagogical goal is to teach students to interrogate AI critically, distinguish between "the AI changed its mind because I made a good argument" and "the AI changed its mind because I pushed back," and develop the disposition to demand logical evidence rather than settle for agreement. The output includes a multi-round questioning sequence using Paul & Elder's question types adapted for AI, an answer drift tracker protocol, a capitulation taxonomy, facilitation notes, and a debrief guide.

## Evidence Foundation

The rest: https://github.com/GarethManning/education-agent-skills/blob/HEAD/skills/ai-literacy/ai-socratic-dialogue-designer/SKILL.md