# Overview

### Introduction

AgentNeo provides comprehensive metrics and evaluation capabilities to assess and optimize your AI applications' performance. The evaluation framework helps you understand your agents' behavior, efficiency, and effectiveness.

### Key Capabilities

* Performance Assessment
* Cost Analysis
* Quality Metrics
* Behavioral Analysis
* Custom Metric Support

### Getting Started with Metrics

```python
from agentneo import Evaluation

# Initialize evaluation
exe = Evaluation(session=neo_session, trace_id=tracer.trace_id)

# Run evaluation
exe.evaluate(metric_list=['goal_decomposition_efficiency'])

# Get results
results = exe.get_results()
```

### Evaluation Process

1. Collect trace data
2. Compute metrics
3. Generate insights
4. Provide recommendations


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://agentneo.raga.ai/evaluation-and-metrics/overview.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
