Summary Generator

Overview

Extraction Process (Socratic Style)

Question 1: Core Concept

"If a student remembers only ONE thing from this lesson tomorrow, what must it be?"

Question 2: Key Mental Models

"What mental frameworks does this lesson install in the student's mind? What 'lenses' do they now see problems through?"

• Cause → Effect relationships
• Decision frameworks ("When X, do Y")
• Conceptual metaphors or analogies

Question 3: Critical Patterns

"What practical techniques or patterns does this lesson teach? What can the student now DO that they couldn't before?"

• Code examples and their purpose
• AI collaboration techniques
• Tools or commands introduced
• Workflows demonstrated

Question 4: AI Collaboration Keys

"How does AI help with this topic? What prompts or collaboration patterns make the difference?"

Question 5: Common Mistakes

"Where do students typically go wrong? What misconceptions does this lesson correct?"

• Explicit "Common Mistakes" sections
• Error examples in the lesson
• Counterintuitive points that contradict assumptions

Question 6: Connections

"What prerequisite knowledge does this build on? Where does this lead next?"

• Builds on: What prior concepts are assumed
• Leads to: What this enables in future lessons

Output Template

### Core Concept
[1-2 sentences from Question 1]

### Key Mental Models
- **[Model Name]**: [Brief explanation]
- **[Model Name]**: [Brief explanation]
- **[Model Name if needed]**: [Brief explanation]

### Critical Patterns
- [Pattern/technique 1]
- [Pattern/technique 2]
- [Pattern/technique 3 if applicable]
- [AI collaboration pattern if applicable]

### Common Mistakes
- [Mistake 1 and why it's wrong]
- [Mistake 2 and why it's wrong]
- [Mistake 3 if applicable]

### Connections
- **Builds on**: [Prior concept/chapter]
- **Leads to**: [Next concept/chapter]

Length Guidelines

proficiency_level

Anti-Patterns (What NOT to Include)

• ❌ Full explanations — Summaries point to concepts, not re-teach them
• ❌ Code examples — The full lesson contains these
• ❌ Practice exercises — Students return to the lesson for practice
• ❌ "What's Next" navigation — Course structure handles this
• ❌ Motivational content — No "Congratulations!" or fluff
• ❌ Layer/Stage labels — Students experience pedagogy, not study it
• ❌ Framework terminology — No "Three Roles", "Layer 2", etc.

File Naming Convention

.summary.md

# Lesson file:
apps/learn-app/docs/05-Python/17-intro/01-what-is-python.md

# Summary file:
apps/learn-app/docs/05-Python/17-intro/01-what-is-python.summary.md

Workflow

1. Read the target lesson file completely
2. Extract the lesson's proficiency level from frontmatter
3. Answer each Socratic question, noting extracted content
4. Compose the summary using the template
5. Validate against anti-patterns checklist
6. Check word count against length guidelines
7. Write the

   .summary.md

   file

Example: Data Types Lesson Summary

### Core Concept
Data types are Python's classification system—they tell Python "what kind of data is this?" and "what operations are valid?"

### Key Mental Models
- **Types → Operations**: Numbers enable math; text enables joining; booleans enable decisions
- **Type Mismatch → Error**: `5 + "hello"` fails because Python can't add numbers to text
- **Type Decision Framework**: Ask "What kind of data?" to determine the right type

### Critical Patterns
- Use `type()` to verify what type Python assigned: `type(42)` returns `<class 'int'>`
- Type hints express intent: `age: int = 25` tells both AI and humans what you expect
- 7 categories cover all data: Numeric, Text, Boolean, Collections, Binary, Special (None)

### Common Mistakes
- Storing numbers as text (`"25"` instead of `25`) prevents math operations
- Forgetting that `0.1 + 0.2` doesn't exactly equal `0.3` (floating point precision)
- Mixing types in operations without explicit conversion

### Connections
- **Builds on**: Python installation and first programs (Chapter 17)
- **Leads to**: Deep dive into numeric types and text handling (Chapters 18-20)