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Evaluations help you understand how well your automation performs, which models work best for your use cases, and how to optimize for cost and reliability. This guide covers both monitoring your own workflows and running comprehensive evaluations.

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Why Evaluations Matter

  • Performance Optimization: Identify which models and settings work best for your specific automation tasks
  • Cost Control: Track token usage and inference time to optimize spending
  • Reliability: Measure success rates and identify failure patterns
  • Model Selection: Compare different LLMs on real-world tasks to make informed decisions

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Comprehensive Evaluations

Evaluations help you systematically test and improve your automation workflows. Stagehand provides both built-in evaluations and tools to create your own. We have 2 types of evals:
  1. Deterministic Evals - These include unit tests, integration tests, and E2E tests that can be run without any LLM inference.
  2. LLM-based Evals - These are evals that test the underlying functionality of Stagehand’s AI primitives.

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Evals CLI

Evals CLI
To run evals, you’ll need to clone the Stagehand repo and set up the CLI.We recommend using Braintrust to help visualize evals results and metrics.
The Stagehand CLI provides a powerful interface for running evaluations. You can run specific evals, categories, or external benchmarks with customizable settings. Evals are grouped into:
  1. Act Evals - These are evals that test the functionality of the act method.
  2. Extract Evals - These are evals that test the functionality of the extract method.
  3. Observe Evals - These are evals that test the functionality of the observe method.
  4. Combination Evals - These are evals that test the functionality of the act, extract, and observe methods together.
  5. Experimental Evals - These are experimental custom evals that test the functionality of the stagehand primitives.
  6. Agent Evals - These are evals that test the functionality of agent.
  7. (NEW) External Benchmarks - Run external benchmarks like WebBench, GAIA, WebVoyager, OnlineMind2Web, and OSWorld.

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Installation

1

Install Dependencies

# From the stagehand root directory
pnpm install
2

Build the CLI

pnpm run build:cli
3

Verify Installation

evals help

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CLI Commands and Options

Basic Commands
# Run all evals
evals run all

# Run specific category
evals run act
evals run extract
evals run observe
evals run agent

# Run specific eval
evals run extract/extract_text

# List available evals
evals list
evals list --detailed

# Configure defaults
evals config
evals config set env browserbase
evals config set trials 5
Command Options
  • -e, --env: Environment (local or browserbase)
  • -t, --trials: Number of trials per eval (default: 3)
  • -c, --concurrency: Max parallel sessions (default: 10)
  • -m, --model: Model override
  • -p, --provider: Provider override
  • --api: Use Stagehand API instead of SDK
Running External Benchmarks
The CLI supports several industry-standard benchmarks: 
# WebBench with filters
evals run benchmark:webbench -l 10 -f difficulty=easy -f category=READ

# GAIA benchmark
evals run b:gaia -s 100 -l 25 -f level=1

# WebVoyager
evals run b:webvoyager -l 50

# OnlineMind2Web
evals run b:onlineMind2Web

# OSWorld
evals run b:osworld -f source=Mind2Web

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Configuration Files

You can view the specific evals in evals/tasks. Each eval is grouped into eval categories based on evals/evals.config.json.

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Viewing eval results

Eval results Eval results are viewable on Braintrust. You can view the results of a specific eval by going to the Braintrust URL specified in the terminal when you run npm run evals. By default, each eval will run five times per model. The “Exact Match” column shows the percentage of times the eval was correct. The “Error Rate” column shows the percentage of times the eval errored out. You can use the Braintrust UI to filter by model/eval and aggregate results across all evals.

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Deterministic Evals

To run deterministic evals, you can run npm run e2e from within the Stagehand repo. This will test the functionality of Playwright within Stagehand to make sure it’s working as expected. These tests are in evals/deterministic and test on both Browserbase browsers and local headless Chromium browsers.

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Creating Custom Evaluations

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Step-by-Step Guide

1

Create Evaluation File

Create a new file in evals/tasks/your-eval.ts:
import { EvalTask } from '../types';

export const customEvalTask: EvalTask = {
  name: 'custom_task_name',
  description: 'Test specific automation workflow',
  
  // Test setup
  setup: async ({ page }) => {
    await page.goto('https://example.com');
  },
  
  // The actual test
  task: async ({ stagehand, page }) => {
    // Your automation logic
    await stagehand.act({ action: 'click the login button' });
    const result = await stagehand.extract({ 
      instruction: 'Get the user name',
      schema: { username: 'string' }
    });
    return result;
  },
  
  // Validation
  validate: (result, expected) => {
    return result.username === expected.username;
  },
  
  // Test cases
  testCases: [
    {
      input: { /* test input */ },
      expected: { username: 'john_doe' }
    }
  ],
  
  // Evaluation criteria
  scoring: {
    exactMatch: true,
    timeout: 30000,
    retries: 2
  }
};
2

Add to Configuration

Update evals/evals.config.json:
{
  "categories": {
    "custom": ["custom_task_name"],
    "existing_category": ["custom_task_name"]
  }
}
3

Run Your Evaluation

# Test your custom evaluation
evals run custom_task_name

# Run the entire custom category
evals run custom

# Run with specific settings
evals run custom_task_name -e browserbase -t 5 -m gpt-4o

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Best Practices for Custom Evals

  • Atomic: Each test should validate one specific capability
  • Deterministic: Tests should produce consistent results
  • Realistic: Use real-world scenarios and websites
  • Measurable: Define clear success/failure criteria
  • Parallel Execution: Design tests to run independently
  • Resource Management: Clean up after each test
  • Timeout Handling: Set appropriate timeouts for operations
  • Error Recovery: Handle failures gracefully
  • Ground Truth: Establish reliable expected outcomes
  • Edge Cases: Test boundary conditions and error scenarios
  • Statistical Significance: Run multiple iterations for reliability
  • Version Control: Track changes to test cases over time

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Troubleshooting Evaluations

Symptoms: Tests fail with timeout errorsSolutions:
  • Increase timeout in taskConfig.ts
  • Use faster models (Gemini 2.5 Flash, GPT-4o Mini)
  • Optimize test scenarios to be less complex
  • Check network connectivity to LLM providers
Symptoms: Same test passes/fails randomlySolutions:
  • Set temperature to 0 for deterministic outputs
  • Increase repetitions for statistical significance
  • Use more capable models for complex tasks
  • Check for dynamic website content affecting tests
Symptoms: Token usage exceeding budgetSolutions:
  • Use cost-effective models (Gemini 2.0 Flash, GPT-4o Mini)
  • Reduce repetitions for initial testing
  • Focus on specific evaluation categories
  • Use local browser environment to reduce Browserbase costs
Symptoms: Results not uploading to dashboardSolutions:
  • Check Braintrust API key configuration
  • Verify internet connectivity
  • Update Braintrust SDK to latest version
  • Check project permissions in Braintrust dashboard
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