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

No annotations are supplied, so the description carries the full behavioral burden. It signals a passive inspection of the machine's environment, but never explicitly states it is read-only/non-destructive, whether it can fail or return partial results (e.g. Vulkan unavailable, no GPU detected), or whether it requires elevated permissions. The enumerated fields do give a reasonable picture of the behavior.

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?

A single front-loaded sentence with a tight enumeration and no filler. Every listed item is substantive information about what the agent will get back.

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?

For a zero-parameter diagnostic with an output schema, the description covers the important ground by naming the data categories returned. The remaining gap is failure/edge-case behavior (missing Vulkan, no discrete GPU), which the output schema may or may not express.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The description correctly makes no attempt to describe inputs.

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?

States a specific verb ('Check') and enumerates the concrete resource fields returned: hardware profile, OS, CPU thread count, Vulkan status, GPU acceleration. This clearly separates it from the image/model-focused siblings (upscale_image, download_model, list_available_models). It stops short of an explicit contrast statement, but the domain difference is obvious.

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?

Usage is only implied: an agent can infer this is a pre-flight hardware probe, plausibly useful before recommend_model or download_model. There is no explicit 'use when' clause, no mention of whether it should be called once per session or cached, and no stated preconditions.

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