LLM Token Usage Analyzer

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Analyze LLM token usage patterns to identify waste and optimization opportunities with savings estimates and implementation priorities.

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Analyze token usage patterns to identify optimization opportunities.

## Usage Data
{{usage_data}}

## Cost Goals
{{cost_goals}}

## Quality Requirements
{{quality_requirements}}

Perform usage analysis:

```python
class TokenUsageAnalyzer:
    def analyze_distribution(self, usage_data: List[UsageRecord]) -> Distribution:
        """
        Analyze:
        - Input vs output token ratio
        - Token count by endpoint
        - Token count by user/team
        - Temporal patterns
        """
        pass
    
    def identify_waste(self, records: List[UsageRecord]) -> List[WasteOpportunity]:
        """
        Find:
        - Repetitive prompts
        - Oversized contexts
        - Low-value requests
        - Retry waste
        """
        pass
    
    def recommend_optimizations(self, analysis: UsageAnalysis) -> List[Recommendation]:
        """Suggest cost reduction strategies"""
        pass
```

Include:
- Visualization of patterns
- Savings estimates
- Implementation priorities
- Monitoring dashboards

Details

Category

Coding

Use Cases

Token analysisCost optimizationUsage patterns

Works Best With

claude-sonnet-4-20250514gpt-4o
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LLM Token Usage Analyzer | Promptsy