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by saucelabs

get_real_device_jobs

Retrieve active jobs running on real devices in the Sauce Labs data center to monitor testing progress and manage device resources.

Instructions

    Get a list of jobs that are actively running on real devices in the data center.
    :param limit: The maximum number of jobs to return.
    :param offset: Limit results to those following this index number. Defaults to 1.
    :param type: Filter results to show manual tests only with LIVE.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions the tool retrieves 'actively running' jobs, implying real-time status, but lacks details on permissions, rate limits, pagination behavior, error handling, or what 'real devices' entails. The description is minimal and misses key behavioral traits for a read operation.

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 appropriately sized with one main sentence and parameter details. It's front-loaded with the core purpose, and each parameter line adds value. However, the formatting with colons and lack of full sentences for params slightly reduces readability.

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 3 parameters with 0% schema coverage and an output schema (which handles return values), the description is moderately complete. It covers parameter basics but lacks behavioral context like permissions or rate limits. For a read tool with output schema, it's adequate but has gaps in usage and transparency.

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%, so the description must compensate. It documents all three parameters with brief semantics: 'limit' as maximum number, 'offset' for pagination with default, and 'type' for filtering to manual tests with 'LIVE'. This adds meaningful context beyond the bare schema, though it could elaborate on 'LIVE' values or parameter interactions.

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

Purpose4/5

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('list of jobs that are actively running on real devices in the data center'). It distinguishes from siblings like 'get_recent_jobs' by specifying 'actively running' and 'real devices', though it doesn't explicitly contrast with all similar tools like 'get_current_jobs_for_tunnel'.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention siblings like 'get_recent_jobs' or 'get_current_jobs_for_tunnel', nor does it specify prerequisites, exclusions, or contextual triggers for usage.

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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