Grade Agent Trajectories And Tool Use Decisions With Agentevals

---
name: "Grade agent trajectories and tool-use decisions with AgentEvals"
slug: "grade-agent-trajectories-and-tool-use-decisions-with-agentevals"
description: "Score whether an agent took a sensible intermediate path, called tools correctly, and reached the outcome without relying only on final-answer checks."
github_stars: 550
verification: "security_reviewed"
source: "https://github.com/langchain-ai/agentevals"
author: "LangChain"
publisher_type: "open_source_project"
category: "Code Quality & Review"
framework: "Custom Agents"
tool_ecosystem:
  github_repo: "langchain-ai/agentevals"
  github_stars: 550
  npm_package: "agentevals"
  npm_weekly_downloads: 251033
---

# Grade agent trajectories and tool-use decisions with AgentEvals

Score whether an agent took a sensible intermediate path, called tools correctly, and reached the outcome without relying only on final-answer checks.

## Prerequisites

Python or TypeScript runtime, agent run outputs or trajectories, optional LLM judge provider

## Installation

Use the upstream install or setup path that matches your environment:
- pip install agentevals
- npm install agentevals @langchain/core
- pip install openai
- npm install openai

Requirements and caveats from upstream:
- <summary>Python</summary>
- python
- [Python Async Support](#python-async-support)

Basic usage or getting-started notes:
- To get started, install agentevals:
- <details open>
- bash

- Source: https://github.com/langchain-ai/agentevals
- Extracted from upstream docs: https://raw.githubusercontent.com/langchain-ai/agentevals/HEAD/README.md

## Documentation

- https://github.com/langchain-ai/agentevals

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/grade-agent-trajectories-and-tool-use-decisions-with-agentevals/)