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by saucelabs

get_test_assets

Retrieve all assets for a test job, including screenshots and logs, using the job ID. Works only for Virtual Device Cloud jobs.

Instructions

    Returns the list of all assets for a test, based on the job ID.

    IMPORTANT: Only use this method with Virtual Device Cloud (VDC) jobs. This will fail
    with a 404 error for Real Device Cloud (RDC) jobs. If you get an error about
    "Real Device job", use get_specific_real_device_job_asset instead.

    To determine job type: RDC jobs typically have device names like "Samsung Galaxy" or "iPhone 14".
    VDC jobs typically have browser names like "chrome", "firefox", or platform names like "Windows 11".

    :param job_id: The Sauce Labs Job ID (VDC jobs only).
    :return: JSON containing a list of assets, from which the URL can be derived.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so the description carries the burden. It discloses that the tool fails with 404 for RDC jobs and returns JSON. It could explicitly state read-only nature, but the provided behavioral context is adequate.

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

Conciseness4/5

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

The description is well-structured with clear sections, bold emphasis, and no redundant sentences. Slightly verbose but effective, earning a 4.

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

Completeness5/5

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

For a single-parameter tool with an output schema, the description covers purpose, usage constraints, parameter description, and return format. It is fully complete for agent decision-making.

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 0%, but the description documents the single parameter 'job_id' with context: 'The Sauce Labs Job ID (VDC jobs only).' This adds meaning beyond the schema's type-only definition.

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 'Returns the list of all assets for a test, based on the job ID.' It specifies the action and resource, and distinguishes from sibling tools by warning against using with RDC jobs and naming the alternative tool.

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

Usage Guidelines5/5

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

It explicitly states 'Only use this method with Virtual Device Cloud (VDC) jobs' and explains the 404 error for RDC jobs, providing the alternative get_specific_real_device_job_asset. It also gives hints to determine job type, offering comprehensive 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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