Skip to main content
When building browser automations in code, you can extract structured data from any page using page.extract with a JSON schema, or by passing a data_extraction_schema to page.agent.run_task. By default, Skyvern returns extracted data in whatever format makes sense for the action. Pass a schema to enforce a specific shape using JSON Schema. If you’re using the Cloud UI workflow editor instead, extraction works through the Extract block. See Block Types and Configuration for setup.

​
Define a schema

Pass a JSON Schema object to page.extract via the schema parameter, or to run_task via data_extraction_schema: 
data = await page.extract(
    "Get the title of the top post",
    schema={
        "type": "object",
        "properties": {
            "title": {
                "type": "string",
                "description": "The title of the top post"
            }
        }
    },
)
The description field in each property helps Skyvern understand what data to extract. Be specific.
description fields drive extraction quality. Vague descriptions like “the data” produce vague results. Be specific: “The product price in USD, without currency symbol.”

​
Schema format

Skyvern uses standard JSON Schema. Common types:
TypeJSON SchemaExample value
String{"type": "string"}"Hello world"
Number{"type": "number"}19.99
Integer{"type": "integer"}42
Boolean{"type": "boolean"}true
Array{"type": "array", "items": {...}}[1, 2, 3]
Object{"type": "object", "properties": {...}}{"key": "value"}
A schema doesn’t guarantee all fields are populated. If the data isn’t on the page, fields return null. Design your code to handle missing values.

​
Build your schema

Use the interactive builder to generate a schema, then copy it into your code.

​
Examples

​
Single value

Extract one piece of information, such as the current price of Bitcoin: 
result = await client.run_task(
    prompt="Get the current Bitcoin price in USD",
    url="https://coinmarketcap.com/currencies/bitcoin/",
    data_extraction_schema={
        "type": "object",
        "properties": {
            "price": {
                "type": "number",
                "description": "Current Bitcoin price in USD"
            }
        }
    }
)
Output (when completed): 
{
  "price": 104521.37
}

​
List of items

Extract multiple items with the same structure, such as the top posts from a news site: 
result = await client.run_task(
    prompt="Get the top 5 posts",
    url="https://news.ycombinator.com",
    data_extraction_schema={
        "type": "object",
        "properties": {
            "posts": {
                "type": "array",
                "description": "Top 5 posts from the front page",
                "items": {
                    "type": "object",
                    "properties": {
                        "title": {
                            "type": "string",
                            "description": "Post title"
                        },
                        "points": {
                            "type": "integer",
                            "description": "Number of points"
                        },
                        "url": {
                            "type": "string",
                            "description": "Link to the post"
                        }
                    }
                }
            }
        }
    }
)
Output (when completed): 
{
  "posts": [
    {
      "title": "Running Claude Code dangerously (safely)",
      "points": 342,
      "url": "https://blog.emilburzo.com/2026/01/running-claude-code-dangerously-safely/"
    },
    {
      "title": "Linux kernel framework for PCIe device emulation",
      "points": 287,
      "url": "https://github.com/cakehonolulu/pciem"
    },
    {
      "title": "I'm addicted to being useful",
      "points": 256,
      "url": "https://www.seangoedecke.com/addicted-to-being-useful/"
    },
    {
      "title": "Level S4 solar radiation event",
      "points": 198,
      "url": "https://www.swpc.noaa.gov/news/g4-severe-geomagnetic-storm"
    },
    {
      "title": "WebAssembly Text Format parser performance",
      "points": 176,
      "url": "https://blog.gplane.win/posts/improve-wat-parser-perf.html"
    }
  ]
}
Arrays without limits extract everything visible on the page. Specify limits in your prompt (e.g., “top 5 posts”) or the array description to control output size.

​
Nested objects

Extract hierarchical data, such as a product with its pricing and availability: 
result = await client.run_task(
    prompt="Get product details including pricing and availability",
    url="https://www.amazon.com/dp/B0EXAMPLE",
    data_extraction_schema={
        "type": "object",
        "properties": {
            "product": {
                "type": "object",
                "description": "Product information",
                "properties": {
                    "name": {
                        "type": "string",
                        "description": "Product name"
                    },
                    "pricing": {
                        "type": "object",
                        "description": "Pricing details",
                        "properties": {
                            "current_price": {
                                "type": "number",
                                "description": "Current price in USD"
                            },
                            "original_price": {
                                "type": "number",
                                "description": "Original price before discount"
                            },
                            "discount_percent": {
                                "type": "integer",
                                "description": "Discount percentage"
                            }
                        }
                    },
                    "availability": {
                        "type": "object",
                        "description": "Stock information",
                        "properties": {
                            "in_stock": {
                                "type": "boolean",
                                "description": "Whether the item is in stock"
                            },
                            "delivery_estimate": {
                                "type": "string",
                                "description": "Estimated delivery date"
                            }
                        }
                    }
                }
            }
        }
    }
)
Output (when completed): 
{
  "product": {
    "name": "Wireless Bluetooth Headphones",
    "pricing": {
      "current_price": 79.99,
      "original_price": 129.99,
      "discount_percent": 38
    },
    "availability": {
      "in_stock": true,
      "delivery_estimate": "Tomorrow, Jan 21"
    }
  }
}

​
Accessing extracted data

How you access extracted data depends on which method you used.

​
page.extract (browser automation)

page.extract returns the extracted data directly as the return value: 
data = await page.extract(
    "Get the top post",
    schema={
        "type": "object",
        "properties": {
            "title": {"type": "string", "description": "Post title"},
            "points": {"type": "integer", "description": "Points"}
        }
    },
)

# data is the extracted result directly
print(f"Title: {data['title']}")
print(f"Points: {data['points']}")

​
run_task (async task)

The extracted data appears in the output field of the completed run. Poll until the task reaches a terminal state, then access the output. 
result = await client.run_task(
    prompt="Get the top post",
    url="https://news.ycombinator.com",
    data_extraction_schema={
        "type": "object",
        "properties": {
            "title": {"type": "string", "description": "Post title"},
            "points": {"type": "integer", "description": "Points"}
        }
    }
)

run_id = result.run_id

while True:
    run = await client.get_run(run_id)

    if run.status in ["completed", "failed", "terminated", "timed_out", "canceled"]:
        break

    await asyncio.sleep(5)

# Access the extracted data
print(f"Output: {run.output}")
If using webhooks, the same output field appears in the webhook payload.

​
Next steps

Actions Reference

All available page actions and agent methods

Build a Browser Automation

Launch a browser, navigate pages, and extract data