Cpu Usage

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

No annotations are provided, so the description carries the full burden and discloses essentially nothing: no statement that it is a read-only, local, side-effect-free collection, no indication of what the returned data looks like (percentages, per-core, load average, sampling window), and no cost or privilege notes. For a diagnostic tool this leaves the agent guessing.

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?

One short, front-loaded sentence with no filler, which is good. But the brevity is under-specification rather than economy — the single clause adds almost no information beyond the title.

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?

With no annotations and no output schema, the description is the only source of truth about what a call returns, and it does not say. An agent cannot tell whether to expect a single percentage, per-core breakdown, or load metrics, which matters when deciding between this and system_status.

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 the baseline of 4 applies. There is no parameter semantics to compensate for and the empty schema fully answers what inputs are needed.

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?

It names a specific verb and resource ("Get CPU usage"), so the agent knows the subject is CPU metrics. But it stops at restating the tool name and says nothing that distinguishes it from memory_usage, disk_usage, or system_status beyond the resource word.

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, when-not-to-use, or alternative named. An agent must infer from the name alone that this is the right call when CPU data is wanted rather than system_status, which may also surface CPU figures.

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