gpu_status

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool's safety is clear. The description adds valuable behavioral context by stating that unsupported fields return null (not omitted), which is a key detail for handling responses. No contradictions with annotations.

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 a single, well-structured sentence that front-loads the key information ('one-shot summary of all AMD GPUs') and then lists the specific metrics. Every word adds value; no redundancy.

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 there are no parameters and no output schema, the description fully explains what the tool returns and how unsupported fields are handled. It is complete for the tool's simple function and provides all necessary information for an agent to use it correctly.

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 has zero parameters, so the input schema fully describes the interface. The description doesn't need to add parameter information. Baseline score of 4 is appropriate as per the calibration guidelines.

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 explicitly states it provides a 'one-shot summary of all AMD GPUs' and lists specific metrics (product name, GPU utilization, VRAM, temperatures, power, fan speed). This clearly distinguishes it from sibling tools like gpu_metrics (presumably detailed metrics) and gpu_processes (process-level info).

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 phrase 'one-shot summary' implies a high-level overview for quick status checking. While it doesn't explicitly state when not to use it or provide alternatives, the sibling tool names offer context. The description could be more explicit about when to use gpu_status versus gpu_metrics or gpu_watch.

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