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run_browsing_task

Execute a web browsing task with an AI agent that operates a browser like a person. Automate form filling, data extraction, or multi-step workflows. Returns a task ID for polling.

Instructions

Execute a one-time web browsing task. The navigator agent runs a browser and operates it like a person. Returns a task_id for polling. Example: 'list employees'. Set browser='local' to use the desktop app with the user's logged-in sessions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesNatural language instruction for the navigator agent. Examples: 'Give me a list of all employees (names and titles) of Yutori', 'Fill out the contact form with my information', 'Extract product prices from this page'
start_urlYesThe URL where the navigator should begin. Example: 'https://yutori.com'
max_stepsNoMaximum number of browser actions (1-100). Default: 25
require_authNoIf true, use an auth-optimized cloud browser provider for login flows. Only applies when browser is 'cloud' (default).
browserNoWhere to run the browser. 'cloud' (default) uses Yutori's cloud browser. 'local' uses Yutori Local with the user's logged-in sessions on the desktop. Requires the desktop app to be running.
output_fieldsNoOptional: Extract structured data as an array of objects with these field names. Example: ['name', 'title', 'email']. If omitted, returns human-readable text. For complex schemas, call the Yutori REST API directly (see example at: https://docs.yutori.com/reference/browsing-create#using-webhooks-and-a-structured-output-schema).
webhook_urlNoHTTPS URL to receive webhook notification when task completes. Must use https://.
webhook_formatNoWebhook payload format: 'scout' (default), 'slack', or 'zapier'
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries full burden. It discloses that the tool returns a task_id for polling, the browser execution options (cloud vs local, with local requiring the desktop app), and webhook usage. It does not cover potential side effects, rate limits, or error states, but covers key behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences plus an example. The core purpose is front-loaded in the first sentence. No fluff or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (8 parameters, no output schema, asynchronous behavior), the description is somewhat sparse. It mentions task_id for polling but does not point to the get_browsing_task_result sibling tool. There is no guidance on error handling or timeouts. With rich schema descriptions, it's minimally complete but has gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The tool description adds value beyond the schema by providing a usage example for the task parameter and a practical tip for the browser parameter, lifting the score to 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Execute a one-time web browsing task' with specific verbs and resources. It also implies distinction from sibling tools like create_scout (recurring) and run_research_task (research vs browsing), making it easy for an agent to select correctly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a concrete example and a note about using browser='local' for desktop integration, offering some usage context. However, it does not explicitly tell when to use this tool versus alternatives like run_research_task or scouts, or provide when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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