TaskProgressionScorer
Measures how effectively the agent progresses toward completing its assigned task. Evaluates logical step sequencing, efficiency of actions taken, and whether the agent is making meaningful progress toward the goal.
Overview
Measures how effectively the agent progresses toward completing its assigned task. Evaluates logical step sequencing, efficiency of actions taken, and whether the agent is making meaningful progress toward the goal.
Use Cases
- Autonomous AI agent evaluation
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 |
|---|---|---|---|
| agent_data.agent_task | str | Yes | The task assigned to the agent |
| agent_data.agent_role | str | Yes | The role of the agent |
| agent_data.system_prompt | str | Yes | The system prompt given to the agent |
| agent_data.agent_response | str | Yes | The response from the agent |
Output Schema
| Field | Type | Description |
|---|---|---|
| score | float | Score (0-10 scale) |
| passed | bool | True if score meets threshold |
| reasoning | str | Detailed evaluation explanation |
| metadata.original_task | str | The extracted original task |
Score Interpretation
Default threshold: 7/10
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Frequently Asked Questions
When should I use this scorer?
Use TaskProgressionScorer when you need to evaluate agent and workflow aspects of your AI outputs. It's particularly useful for autonomous ai agent evaluation.
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 7 can be customized when configuring the scorer.
Quick Info
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