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Documentation Index

Fetch the complete documentation index at: https://mintlify.com/steerlabs/opensteer/llms.txt

Use this file to discover all available pages before exploring further.

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Method Signature

agent.execute(instructionOrOptions: string | OpensteerAgentExecuteOptions): Promise<OpensteerAgentResult>
Execute an agent task with a natural language instruction. The agent will analyze the browser state, decide on actions, and execute them until the task is complete or max steps is reached.

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Parameters

You can pass either a string instruction or an options object:

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String Parameter

await agent.execute('Search for OpenSteer documentation')

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Options Object

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instruction
string
required
Natural language instruction describing the task to complete. Must be a non-empty string.
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maxSteps
number
default:20
Maximum number of actions the agent can take. Must be a positive integer. Prevents infinite loops and controls execution cost.
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highlightCursor
boolean
default:false
When true, displays a red cursor overlay at the action coordinates during execution. Useful for debugging and demonstrations.

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Return Type

Returns a Promise<OpensteerAgentResult> with the following fields:
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success
boolean
required
Whether the agent execution completed without errors. false indicates a failure (API error, invalid action, etc.).
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completed
boolean
required
Whether the agent finished the task successfully. false when max steps reached before completion.
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message
string
required
Human-readable message describing the result. Contains completion message or error details.
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actions
OpensteerAgentAction[]
required
Array of actions taken by the agent during execution. Each action includes type, coordinates, reasoning, and metadata.
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usage
OpensteerAgentUsage | undefined
Token and time usage statistics for the execution.
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provider
OpensteerAgentProvider
required
The provider used for execution: 'openai', 'anthropic', or 'google'.
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model
string
required
Full model name in provider/model format (e.g., 'openai/computer-use-preview').

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Action Types

Each action in the actions array includes:
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type
string
required
Action type: 'click', 'type', 'scroll', 'navigate', 'wait', 'screenshot', 'finish'
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reasoning
string | undefined
Agent’s reasoning for taking this action.
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x
number | undefined
X coordinate for click actions.
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y
number | undefined
Y coordinate for click actions.
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text
string | undefined
Text input for type actions.
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scrollX
number | undefined
Horizontal scroll delta.
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scrollY
number | undefined
Vertical scroll delta.
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url
string | undefined
URL for navigate actions.
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timeMs
number | undefined
Wait duration in milliseconds.

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Examples

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Basic Usage

import { Opensteer } from 'opensteer'

const browser = new Opensteer()
await browser.launch()
await browser.goto('https://example.com')

const agent = browser.agent({
  mode: 'cua',
  model: 'openai/computer-use-preview'
})

const result = await agent.execute('Click the login button')

if (result.success && result.completed) {
  console.log('✓ Task completed:', result.message)
  console.log('Actions taken:', result.actions.length)
} else if (result.success && !result.completed) {
  console.warn('⚠ Max steps reached before completion')
} else {
  console.error('✗ Execution failed:', result.message)
}

await browser.close()

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With Options

const result = await agent.execute({
  instruction: 'Fill out the contact form with test data',
  maxSteps: 30,
  highlightCursor: true
})

console.log('Provider:', result.provider)
console.log('Model:', result.model)

if (result.usage) {
  console.log('Input tokens:', result.usage.inputTokens)
  console.log('Output tokens:', result.usage.outputTokens)
  console.log('Inference time:', result.usage.inferenceTimeMs, 'ms')
}

for (const action of result.actions) {
  console.log(`${action.type}: ${action.reasoning || 'N/A'}`)
}

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Error Handling

try {
  const result = await agent.execute('Complete checkout process')
  
  if (!result.success) {
    throw new Error(`Agent failed: ${result.message}`)
  }
  
  if (!result.completed) {
    console.warn('Task incomplete - may need more steps')
  }
  
  return result
} catch (error) {
  console.error('Execution error:', error)
  throw error
}

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Analyzing Actions

const result = await agent.execute('Search for products')

const clickActions = result.actions.filter(a => a.type === 'click')
const typeActions = result.actions.filter(a => a.type === 'type')
const navigateActions = result.actions.filter(a => a.type === 'navigate')

console.log(`Clicks: ${clickActions.length}`)
console.log(`Text inputs: ${typeActions.length}`)
console.log(`Navigations: ${navigateActions.length}`)

// Print reasoning for each action
for (const action of result.actions) {
  if (action.reasoning) {
    console.log(`[${action.type}] ${action.reasoning}`)
  }
}

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Notes

  • Agent execution is slower and more expensive than direct actions
  • Always set appropriate maxSteps to prevent runaway execution
  • Check both success and completed flags in the result
  • The usage field may be undefined depending on the provider
  • Actions are executed sequentially with waitBetweenActionsMs delay between them
  • The agent cannot be executed concurrently - only one execution at a time per agent instance

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