# Prompt Template Optimizer AI Agent Connect

> A deterministic utility for balancing LLM token efficiency against semantic importance.

## Overview
- **Category:** developer-tools
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_JwfSuEoCWCwZfbckPUWbQKyr1AaSXNGLXwvA5cyv/ai-agent-connect
- **Tags:** tokens, efficiency, llm, optimization, templates

## Description

This MCP server provides mathematical precision for prompt engineering. Use `optimize_template` to find the ideal balance between token savings and semantic quality by analyzing the importance-to-token ratio of your prompt sections. It also includes tools like `analyze_prompt_efficiency` to evaluate performance and `calculate_variable_overhead` to estimate the hidden costs of dynamic variable injection. It is designed to help developers find the mathematical sweet spot for LLM context window management.

## Tools

### optimize_template
Calculate the most efficient version of a prompt template based on a specific strategy

### analyze_prompt_efficiency
Evaluate a single prompt configuration against established performance benchmarks

### calculate_variable_overhead
Estimate the hidden cost of using templates with many dynamic variables

## Prompt Examples

**Prompt:** 
```
Optimize this prompt: 500 base tokens, sections: 'System' (100 tokens, 0.9 importance), 'Context' (300 tokens, 0.5 importance), 'Task' (100 tokens, 0.8 importance) using the balance strategy.
```

**Response:** 
```
The optimized prompt retains the 'System' and 'Task' sections, resulting in 200 tokens with a high efficiency score.
```

**Prompt:** 
```
Calculate the overhead for a template with 5 variables and an average length of 50 tokens per variable.
```

**Response:** 
```
The total variable cost is 250 tokens.
```

**Prompt:** 
```
Evaluate a prompt with 1000 tokens, 0.8 aggregate importance, and 10 variables.
```

**Response:** 
```
The efficiency score is 0.0008, which results in a Low utility rating.
```

## Frequently Asked Questions

**How does the optimization strategy work?**
The tool calculates the ratio of importance to token count for each section. Depending on your chosen strategy, it will either prioritize minimizing tokens, maximizing quality, or finding a balance between the two.

**Can I set a specific token limit?**
Yes, you can provide a target token limit to ensure the optimized prompt stays within your desired context window size.

**What is variable injection cost?**
It is the estimated increase in token count caused by replacing template placeholders with actual data during runtime.