get_test_assets

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the tool will fail with a 404 error for RDC jobs, it returns JSON containing a list of assets, and URLs can be derived from the response. It doesn't mention rate limits, authentication needs, or pagination, but provides substantial operational context.

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

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

The description is well-structured and efficiently organized. It starts with the core purpose, immediately follows with critical usage warnings and alternatives, provides practical implementation guidance, and ends with parameter and return documentation. Every sentence serves a clear purpose with zero wasted words.

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

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

Given the tool's moderate complexity (single parameter, no annotations, but with output schema), the description provides excellent contextual completeness. It covers purpose, usage constraints, error conditions, alternatives, parameter semantics, and return format. With an output schema present, it appropriately doesn't need to detail the return structure beyond indicating it's JSON containing asset lists.

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

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

With 0% schema description coverage for the single parameter, the description fully compensates by providing the :param job_id documentation that specifies 'The Sauce Labs Job ID (VDC jobs only).' This adds crucial semantic context beyond the schema's basic type information, clearly indicating the parameter's purpose and constraints.

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

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 specific verb ('Returns') and resource ('list of all assets for a test'), and distinguishes it from sibling tools by specifying it's for VDC jobs only. It explicitly contrasts with get_specific_real_device_job_asset for RDC jobs, making the distinction clear.

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

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

The description provides explicit guidance on when to use this tool ('Only use this method with Virtual Device Cloud (VDC) jobs') and when not to use it ('will fail with a 404 error for Real Device Cloud (RDC) jobs'). It names the alternative tool (get_specific_real_device_job_asset) and includes practical heuristics for determining job type based on device/browser names.

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