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

With no annotations, the description carries the full behavioral burden. It discloses scope ('local machine') and implies a read-only snapshot via 'Returns', but says nothing about permissions, cost, latency, or whether the values are instantaneous vs. averaged. Adequate but not rich given the zero annotation coverage.

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?

Two tight sentences with zero padding: the first defines what is returned, the second defines when to use it. Information is front-loaded and every clause earns its place.

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, low-complexity read tool with no output schema, the description covers the essentials by naming the three metric families returned and giving a use case. It stops short of describing units, formatting, or refresh semantics, which an agent would need for precise downstream reasoning.

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 no parameters and the schema is fully self-describing, so the baseline of 4 applies. The description correctly adds nothing parameter-related because there is nothing to disambiguate.

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 ('Returns') and resource ('CPU, RAM, and Disk utilisation') with clear scope ('for the local machine'), so an agent immediately knows what data comes back. It does not explicitly differentiate itself from the sibling get_top_processes, but the resource distinction is implicit and clear enough.

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?

Gives concrete when-to-use guidance: pre-flight checks before heavy builds, containers, or model inference. It supplies no explicit exclusions or named alternatives, which keeps it short of a 5, but the usage context is unambiguous.

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