Step 1: Gather Chapter Content
Read all lesson files in the chapter directory:
```bash
ls -la /*.md | grep -v summary | grep -v README | grep -v quiz
```
For each lesson file, extract:
- YAML frontmatter (learning objectives, cognitive load, skills, layer)
- Word count
- Section structure (headings)
- Try With AI prompts
- Hands-on exercises
- Code examples
Step 2: Student Perspective Analysis
Evaluate as a beginner encountering this content for the first time.
#### 2.1 Engagement Score (1-10)
| Score | Criteria |
|-------|----------|
| 9-10 | Compelling hook, real-world relevance clear, I want to keep reading |
| 7-8 | Interesting enough, some engaging moments, minor dry spots |
| 5-6 | Functional but forgettable, reads like documentation |
| 3-4 | Boring, walls of text, no compelling reason to continue |
| 1-2 | Would abandon after first section |
Check for:
- Opening hook (does first paragraph grab attention?)
- Real-world scenarios (why does this matter to ME?)
- Story/narrative flow vs disconnected facts
- Visual breaks (diagrams, tables, code blocks)
- Pacing variety (concept β hands-on β concept)
- Comparative Value (vs alternatives like VS Code/Copilot)
#### 2.2 Length Assessment
| Verdict | Criteria |
|---------|----------|
| Too Short | Missing examples, concepts unexplained, abrupt endings, "I don't understand" |
| Just Right | Each concept has sufficient depth, examples clarify, natural flow |
| Too Long | Repetitive explanations, over-elaborated points, could cut 30%+ |
Word count benchmarks:
- Conceptual lesson: 1,000-1,400 words
- Hands-on lesson: 1,200-1,600 words
- Installation/setup: 800-1,200 words (focused)
- Capstone: 1,400-1,800 words
#### 2.3 Clarity Score (1-10)
| Score | Criteria |
|-------|----------|
| 9-10 | Crystal clear, no re-reading needed, "aha" moments |
| 7-8 | Mostly clear, occasional re-read for complex parts |
| 5-6 | Understandable with effort, some confusing sections |
| 3-4 | Frequently confused, missing context, jargon unexplained |
| 1-2 | Cannot follow, assumes knowledge I don't have |
Check for:
- Jargon introduced before defined
- Logical flow between paragraphs
- Transitions between sections
- Prerequisites assumed vs stated
- Safety Checks: No concatenated commands or risky copy-pastes
#### 2.4 Hands-On Effectiveness (1-10)
| Score | Criteria |
|-------|----------|
| 9-10 | Clear steps, achievable, builds confidence, "I did it!" |
| 7-8 | Mostly clear, minor ambiguity, successful completion likely |
| 5-6 | Workable but confusing steps, may need to troubleshoot |
| 3-4 | Missing steps, unclear what to do, likely to get stuck |
| 1-2 | Cannot complete without external help |
Check for:
- Step-by-step instructions (numbered, clear)
- Expected output/results shown
- Troubleshooting guidance
- Connection to concepts just learned
#### 2.5 Progression Clarity (1-10)
| Score | Criteria |
|-------|----------|
| 9-10 | Clear path from start to mastery, each lesson builds on previous |
| 7-8 | Generally progressive, minor jumps between lessons |
| 5-6 | Some logical progression, noticeable gaps |
| 3-4 | Disconnected lessons, unclear how they relate |
| 1-2 | Random ordering, no clear learning path |
Check for:
- Opening connections ("In Lesson N-1, you learned X. Now...")
- Running example threaded through chapter
- Skills building on each other
- Clear "what's next" at lesson end
#### 2.6 Confidence Score (1-10)
| Score | Criteria |
|-------|----------|
| 9-10 | "I can definitely do this now" - ready to apply independently |
| 7-8 | "I mostly understand and could figure out the rest" |
| 5-6 | "I kind of get it but would need help applying it" |
| 3-4 | "I'm confused about when/how to use this" |
| 1-2 | "I have no idea what I just read" |
Check for:
- Practice opportunities before moving on
- Verification steps ("you should see X")
- Real-world application examples
- "Try it yourself" prompts
Step 3: Teacher Perspective Analysis
Evaluate as an instructional designer assessing pedagogical soundness.
#### 3.1 Learning Objectives Quality (1-10)
| Score | Criteria |
|-------|----------|
| 9-10 | SMART objectives, measurable, aligned to content and assessment |
| 7-8 | Clear objectives, mostly measurable, good alignment |
| 5-6 | Objectives present but vague or partially aligned |
| 3-4 | Weak objectives, not measurable, poor alignment |
| 1-2 | Missing or meaningless objectives |
Check for:
- Bloom's taxonomy verb alignment (Remember β Create)
- Measurable criteria ("can explain", "can create", "can distinguish")
- Assessment method specified
- Objectives actually taught in lesson content
#### 3.2 Cognitive Load Management (1-10)
| Score | Criteria |
|-------|----------|
| 9-10 | Appropriate concepts for level, well-scaffolded, no overload |
| 7-8 | Generally appropriate, minor overload moments |
| 5-6 | Some cognitive overload, too many concepts at once |
| 3-4 | Significant overload, concepts piled without consolidation |
| 1-2 | Overwhelming, no chance of retention |
Benchmarks by proficiency:
- A1-A2: 3-5 new concepts per lesson
- B1-B2: 5-7 new concepts per lesson
- C1-C2: 7-10 new concepts per lesson
Check for:
- New concepts counted in frontmatter
- Concepts introduced one at a time
- Practice before new concept introduced
- Chunking of complex procedures
#### 3.3 Scaffolding Quality (1-10)
| Score | Criteria |
|-------|----------|
| 9-10 | Perfect progression, each concept builds on previous, no gaps |
| 7-8 | Good scaffolding, minor jumps that students can bridge |
| 5-6 | Some scaffolding gaps, requires prior knowledge not taught |
| 3-4 | Significant gaps, assumes knowledge not in prerequisites |
| 1-2 | No scaffolding, concepts appear randomly |
Check for:
- Prerequisites listed and actually prerequisite
- Concepts introduced before used
- Increasing complexity curve
- Prior knowledge activated before new content
#### 3.4 Pedagogical Layer Appropriateness (1-10)
| Layer | Expected Characteristics |
|-------|-------------------------|
| L1 (Foundation) | Manual-first, understand before automate, no AI shortcuts |
| L2 (Collaboration) | AI as Teacher/Student/Co-Worker, learning through interaction |
| L3 (Intelligence) | Pattern recognition, creating reusable intelligence (skills/subagents) |
| L4 (Orchestration) | Capstone, combining components, spec-driven development |
Check for:
- Layer declared in frontmatter
- Content matches layer expectations
- Layer progression through chapter (L1 β L2 β L3 β L4)
- No premature automation (L3 content in early lessons)
#### 3.5 Try With AI Effectiveness (1-10)
| Score | Criteria |
|-------|----------|
| 9-10 | Prompts directly extend lesson, specific, build skills |
| 7-8 | Good prompts, mostly connected to content |
| 5-6 | Generic prompts, loosely connected |
| 3-4 | Copy-paste prompts, don't match lesson |
| 1-2 | Missing or irrelevant prompts |
Check for:
- 2-3 prompts per lesson (not 1, not 5+)
- Prompts reference lesson content specifically
- Progressive difficulty across prompts
- "What's you're learning" explanations present
#### 3.6 Assessment/Verification Quality (1-10)
| Score | Criteria |
|-------|----------|
| 9-10 | Clear verification at each step, students know if they succeeded |
| 7-8 | Good verification for most exercises |
| 5-6 | Some verification, students may be unsure of success |
| 3-4 | Weak verification, students can't tell if they're on track |
| 1-2 | No verification, students have no idea if they succeeded |
Check for:
- "Expected output" shown for commands
- "You should see X" confirmations
- Error states explained
- End-of-lesson checkpoint