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.

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

With no annotations, the description carries the full behavioral burden, yet it only states the sort criterion. It doesn't say whether the result is a live snapshot or averaged, whether ties are broken deterministically, or whether privileges are required to see other users' processes.

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 tight sentence with the ranking criterion front-loaded and no filler. It is efficient, though arguably too terse given the absence of annotations.

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 one-parameter read tool with no output schema, the core contract is covered. Still, ordering behavior and result format go unmentioned, leaving gaps that annotations would otherwise have filled.

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?

Schema coverage is 100% and the single limit parameter is fully documented in the schema, so the baseline is 3. The description's 'N processes' merely restates the limit parameter without adding format or behavior detail.

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 states a specific verb (returns), resource (processes), and ranking criterion (highest CPU usage), which is enough to tell it apart from a metrics-aggregation sibling. It stops short of explicitly naming or contrasting with get_system_metrics, so sibling differentiation is only implied.

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?

There is no when-to-use guidance, no prerequisites, and no mention of the get_system_metrics alternative for aggregate CPU data. The agent must infer that this is for per-process inspection rather than system-level totals.

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