token-consumption-and-alternative-sequence.md•10.2 kB
# Token Consumption Analysis & Alternative Sequence Evaluation
**Date**: July 11, 2025
**Analysis**: Current vs Alternative Approach
---
## 1. Token Consumption Analysis
### Current Prevention-First Approach
#### Token Count Breakdown:
- **API Requirements Catalog**: ~14,593 characters (~3,650 tokens)
- **Widget Catalog**: ~8,000 characters (~2,000 tokens)
- **Educational Guidance**: ~4,000 characters (~1,000 tokens)
- **Instructions**: ~3,000 characters (~750 tokens)
- **Total per guidance request**: ~**8,400 tokens**
#### Token Consumption Concerns ✅/❌
**Pros:**
- ✅ **One-time cost**: Guidance consumed once per lesson creation
- ✅ **Prevention value**: Prevents multiple retry cycles (saves tokens)
- ✅ **Higher success rate**: Less validation/correction rounds
**Cons:**
- ❌ **High upfront cost**: ~8,400 tokens per lesson request
- ❌ **Information overload**: Claude receives all widget specs even if only using 3-4
- ❌ **Static delivery**: Same large payload regardless of lesson complexity
#### Real Token Impact:
**Single lesson creation:**
- Current: 8,400 (guidance) + 2,000 (content) + 1,500 (validation/format) = **~12,000 tokens**
- With retries: 8,400 + 2,000 + (3 x 1,500 retries) = **~15,000 tokens**
**Assessment**: ❌ **YES, unnecessarily high token consumption**
---
## 2. Alternative Sequence Feasibility Analysis
### Proposed Just-In-Time (JIT) Sequence
```
a. Understand user's request [~500 tokens]
b. Obtain overall guidance [~1,500 tokens]
c. Create content as Claude sees fit [~2,000 tokens]
d. Analyze content for widget mapping [~800 tokens]
e. Map content segments to widget types [~600 tokens]
f. Get detailed requirements for selected widgets [~2,000 tokens]
g. Format content per widget requirements [~1,000 tokens]
h. Create final composition [~800 tokens]
i. Save via API [~400 tokens]
j. Display in Composer [~300 tokens]
```
**Total estimated tokens**: ~**9,900 tokens** (17% reduction)
### Feasibility Assessment: ✅ **HIGHLY FEASIBLE**
#### Technical Implementation:
**Step b - Overall Guidance (Lightweight)**
```javascript
getOverallGuidance() {
return {
availableWidgetTypes: ['head-1', 'text-1', 'quiz-1', 'flashcards-1', 'image-1', 'video-1', 'list-1', 'gallery-1', 'hotspots-1'],
educationalPrinciples: ['cognitive load balance', 'learning progression', 'assessment integration'],
lengthGuidelines: { lessonDuration: 50, textMinimum: 20, quizQuestions: '1-10' },
workflow: 'Create content freely, then we\'ll map to optimal widgets'
};
}
```
**Step d-e - Content Analysis & Widget Mapping**
```javascript
analyzeContentForWidgets(claudeContent) {
// Parse Claude's content to identify:
// - Introduction sections → head-1
// - Explanatory text → text-1
// - Questions → quiz-1
// - Term definitions → flashcards-1
// - Lists → list-1
// - Images needed → image-1
// - Interactive elements → hotspots-1
}
```
**Step f - Just-In-Time Widget Requirements**
```javascript
getWidgetRequirements(selectedWidgetTypes) {
// Return ONLY the API requirements for widgets actually being used
// Instead of all 9 widget types, return only 3-4 needed
return selectedWidgetTypes.map(type => this.apiFieldMappings[type]);
}
```
#### Advantages of JIT Approach:
**🎯 Token Efficiency**
- ✅ **Selective guidance**: Only widget requirements actually needed
- ✅ **Smaller payloads**: ~2,000 tokens vs ~8,400 tokens for guidance
- ✅ **Content-driven**: Requirements based on what Claude created
**🧠 Cognitive Benefits**
- ✅ **Natural creation**: Claude creates content without format constraints
- ✅ **Cleaner separation**: Content creation vs technical formatting
- ✅ **Less overwhelm**: Claude focuses on education first, format second
**🔧 Technical Benefits**
- ✅ **Intelligent mapping**: System analyzes content to suggest optimal widgets
- ✅ **Precise requirements**: Only relevant API specifications provided
- ✅ **Adaptive**: Different requirements for different lesson types
#### Potential Challenges:
**⚠️ Content Analysis Complexity**
- Need sophisticated content parsing to map to widgets
- Risk of suboptimal widget selection by analysis algorithm
**⚠️ Two-Stage Validation**
- Content validation + Widget format validation
- Potential for more complex error handling
**⚠️ Multi-Step Dependencies**
- Steps d-g depend on successful content analysis
- Failure in widget mapping affects downstream steps
---
## 3. Recommended Implementation Strategy
### Hybrid Approach: **Smart JIT with Fallback**
#### Phase 1: Lightweight Guidance
```javascript
getSmartGuidance(userPrompt) {
// Analyze user prompt to predict likely widgets needed
const predictedWidgets = this.predictWidgetsFromPrompt(userPrompt);
return {
basicGuidelines: { /* educational principles, length requirements */ },
suggestedWidgets: predictedWidgets,
detailedRequirements: null // Provided later in JIT fashion
};
}
```
#### Phase 2: Content Creation
```javascript
// Claude creates content naturally without overwhelming constraints
createEducationalContent(prompt, basicGuidelines);
```
#### Phase 3: Intelligent Widget Mapping
```javascript
analyzeAndMapContent(claudeContent) {
return {
suggestedMapping: [
{ contentSegment: "Introduction paragraph", recommendedWidget: "text-1" },
{ contentSegment: "Question about photosynthesis", recommendedWidget: "quiz-1" },
{ contentSegment: "Term definitions", recommendedWidget: "flashcards-1" }
],
confidence: 0.95
};
}
```
#### Phase 4: JIT Widget Requirements
```javascript
getSpecificWidgetRequirements(mappedWidgets) {
// Return only the precise API requirements for selected widgets
return mappedWidgets.map(widget => ({
type: widget.type,
apiRequirements: this.apiFieldMappings[widget.type],
contentSegment: widget.contentSegment
}));
}
```
### Implementation Breakdown:
**New Tools Structure:**
1. **`get_smart_guidance`** - Lightweight educational guidance (~1,500 tokens)
2. **`analyze_content_for_widgets`** - Intelligent content→widget mapping (~800 tokens)
3. **`get_widget_requirements`** - JIT API requirements for selected widgets (~2,000 tokens)
4. **`format_for_composer`** - Enhanced to use specific requirements
5. **`save_composition_api`** - Unchanged
6. **`open_composition_editor`** - Unchanged
**Token Savings:**
- **Current**: ~8,400 tokens for comprehensive guidance
- **JIT Hybrid**: ~4,300 tokens distributed across multiple efficient calls
- **Savings**: ~**48% reduction** in guidance tokens
---
## 4. Technical Implementation Plan
### Tool Modifications Required:
#### 1. New: `get_smart_guidance` Tool
```javascript
// Replaces massive get_lesson_guidance with intelligent lightweight version
async getSmartGuidance(args) {
const { prompt, subject, gradeLevel } = args;
// Predict likely widgets from prompt analysis
const predictedWidgets = this.predictWidgetsFromPrompt(prompt, subject);
return {
basicGuidelines: this.getBasicEducationalGuidelines(subject, gradeLevel),
suggestedWidgets: predictedWidgets,
workflow: "Create educational content naturally, then we'll optimize widget mapping"
};
}
```
#### 2. New: `analyze_content_for_widgets` Tool
```javascript
async analyzeContentForWidgets(args) {
const { claudeContent } = args;
const mapping = this.intelligentWidgetMapper.analyzeContent(claudeContent);
return {
suggestedMapping: mapping,
rationale: "Based on content analysis and educational best practices"
};
}
```
#### 3. New: `get_widget_requirements` Tool
```javascript
async getWidgetRequirements(args) {
const { selectedWidgets } = args;
// Return ONLY requirements for widgets actually being used
const requirements = selectedWidgets.map(widget =>
this.apiRequirements.getSpecificRequirements(widget.type)
);
return { widgetRequirements: requirements };
}
```
### Workflow Comparison:
#### Current Workflow:
```
1. get_lesson_guidance [8,400 tokens] → Complete specifications
2. validate_lesson_data → Validation
3. format_for_composer → Field conversion
4. save_composition_api → API save
5. open_composition_editor → Navigation
```
#### JIT Workflow:
```
1. get_smart_guidance [1,500 tokens] → Basic guidelines
2. analyze_content_for_widgets [800 tokens] → Widget mapping
3. get_widget_requirements [2,000 tokens] → Specific API requirements
4. validate_lesson_data → Validation
5. format_for_composer → Minimal conversion needed
6. save_composition_api → API save
7. open_composition_editor → Navigation
```
---
## 5. Recommendation
### ✅ **IMPLEMENT JIT HYBRID APPROACH**
**Rationale:**
1. **Token Efficiency**: ~48% reduction in guidance tokens
2. **Better UX**: Claude creates content naturally without overwhelming constraints
3. **Precision**: API requirements provided only for widgets actually used
4. **Maintainability**: Smaller, focused tool responsibilities
5. **Scalability**: Easily add new widgets without increasing base guidance size
### Implementation Priority:
1. **Phase 1**: Implement basic JIT tools (1-2 days)
2. **Phase 2**: Add intelligent content analysis (2-3 days)
3. **Phase 3**: Optimize widget prediction algorithms (1-2 days)
4. **Phase 4**: Performance testing and refinement (1 day)
### Expected Benefits:
- **48% token reduction** in guidance phase
- **More natural content creation** for Claude
- **Precise API requirements** delivered just-in-time
- **Better maintainability** with focused tool responsibilities
- **Improved scalability** for adding new widget types
The proposed JIT approach is not only feasible but superior to the current prevention-first approach in both token efficiency and user experience.
---
**Analysis Complete**: July 11, 2025
**Recommendation**: ✅ Implement JIT Hybrid Approach
**Expected Token Savings**: 48% in guidance phase
**Implementation Effort**: ~1 week for complete migration