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Socratic Questioning

  • 62 installs
  • 28 repo stars
  • Updated June 29, 2026
  • nickcrew/claude-ctx-plugin

Helps with ai & agent building tasks.

About

socratic-questioning is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • socratic-questioning
  • AI & Agent Building
  • AI-coding skill

Socratic Questioning by the numbers

  • 62 all-time installs (skills.sh)
  • +1 installs in the week ending Jul 26, 2026 (Skillselion tracking)
  • Ranked #6,163 of 16,556 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
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Listed on Skillselion
Installs62
repo stars28
Last updatedJune 29, 2026
Repositorynickcrew/claude-ctx-plugin

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

Socratic Questioning

Guide developers toward discovery through strategic questioning rather than direct instruction. Covers Clean Code principles, GoF design patterns, and architectural trade-offs using progressive, level-adaptive questioning techniques.

When to Use This Skill

  • Coaching developers on Clean Code or design pattern concepts
  • Facilitating design discussions where the team needs to discover trade-offs
  • Helping developers identify code smells and refactoring opportunities
  • Teaching programming principles through guided discovery
  • Running code review sessions focused on learning, not just fixing

Quick Reference

ResourcePurposeLoad when
references/questioning-techniques.mdSocratic method for code, question types, scaffolding progressionStarting a discovery session
references/facilitation-patterns.mdClean Code discovery, GoF pattern recognition, trade-off explorationDiscussing specific patterns or principles

---

Workflow

Phase 1: Assess       → Determine learner level, goals, prior knowledge
Phase 2: Explore      → Lead discovery with layered questions
Phase 3: Consolidate  → Summarize insights, propose exercises, outline next steps

---

Phase 1: Assess

Before asking questions, understand the learner:

1. Gauge level -- beginner (concrete observations), intermediate (pattern recognition), advanced (synthesis and application) 2. Identify goals -- what does the learner want to understand or improve? 3. Map prior knowledge -- what principles do they already apply? 4. Choose strategy -- select questioning depth and scaffolding level

---

Phase 2: Explore

Lead discovery through layered questioning:

Core Progression

Observe  → "What do you notice about [specific aspect]?"
Analyze  → "Why might that be important?"
Abstract → "What principle could explain this?"
Apply    → "How would you apply this principle elsewhere?"

Principles

  • Ask, don't tell -- guide toward the insight, don't state it directly
  • Build incrementally -- each question builds on the previous answer
  • Validate discoveries -- confirm insights without judgment
  • Name after discovery -- only name a pattern/principle after the learner identifies the concept

Knowledge Revelation Timing

  • After discovery: "What you've discovered is called..."
  • Confirming: "Robert Martin describes this as..."
  • Contextualizing: "You'll see this principle at work when..."
  • Applying: "Try applying this to..."

---

Phase 3: Consolidate

Close the learning loop:

1. Summarize -- have the learner articulate what they discovered 2. Connect -- link the discovery to broader principles and patterns 3. Practice -- propose an exercise that applies the new understanding 4. Plan -- outline what to explore next based on gaps revealed

---

Session Types

SessionFocusFlow
Code ReviewApply Clean Code to existing codeObserve → Identify issues → Discover principles → Improve
Pattern DiscoveryRecognize GoF patterns in codeAnalyze behavior → Identify structure → Discover intent → Name pattern
Principle ApplicationApply learned principles to new scenariosPresent scenario → Recall principles → Apply → Validate

---

Understanding Checkpoints

Track learner progress through these milestones:

CheckpointEvidence
ObservationLearner identifies relevant code characteristics
Pattern recognitionLearner sees recurring structures or behaviors
Principle connectionLearner connects observations to programming principles
Application abilityLearner applies principles to new scenarios
Teaching abilityLearner can explain the principle to others

---

Anti-Patterns

  • Do not lecture -- if you're explaining more than asking, recalibrate
  • Do not reveal the answer before the learner has a chance to discover it
  • Do not ask leading questions that have only one acceptable answer
  • Do not skip levels -- ensure the learner has a solid foundation before advancing
  • Do not judge wrong answers -- redirect with a follow-up question instead

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