TechnicalAccuracyScorer
Evaluates technical accuracy of domain-specific responses. Assesses correctness of technical concepts, procedures, terminology, and quantitative information.
Overview
Evaluates technical accuracy of domain-specific responses. Assesses correctness of technical concepts, procedures, terminology, and quantitative information.
Use Cases
- Accuracy benchmarking and validation
How It Works
This scorer uses LLM-as-Judge technology to evaluate responses. It prompts a large language model with specific evaluation criteria and the content to assess, then analyzes the LLM's judgment to produce a score and detailed reasoning.
Input Schema
| Parameter | Type | Required | Description |
|---|---|---|---|
| output_text | str | Yes | Technical response to evaluate |
| input_text | str | Yes | Technical question |
| context | dict | str | No | Domain knowledge/reference |
Output Schema
| Field | Type | Description |
|---|---|---|
| score | float | Technical accuracy score (0-10) |
| passed | bool | True if technically accurate |
| reasoning | str | Technical analysis |
| metadata | dict | Technical issues if any |
Score Interpretation
Default threshold: 8/10
Related Scorers
Frequently Asked Questions
When should I use this scorer?
Use TechnicalAccuracyScorer when you need to evaluate quality and llm-judge aspects of your AI outputs. It's particularly useful for accuracy benchmarking and validation.
Why doesn't this scorer need expected output?
This scorer evaluates quality aspects that don't require comparison against a reference answer. It uses the system prompt and context as the implicit ground truth.
Can I customize the threshold?
Yes, the default threshold of 8 can be customized when configuring the scorer.
Quick Info
Ready to try TechnicalAccuracyScorer?
Start evaluating your AI agents with Noveum.ai's comprehensive scorer library.
Explore More Scorers
Discover 68+ LLM-as-Judge scorers for comprehensive AI evaluation
