gpu_processes

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

No annotations are provided, so the description must carry the transparency burden. 'List' implies a read-only operation, but the description does not mention prerequisites like NVIDIA drivers, the output format details, or failure conditions. It provides basic transparency but lacks depth.

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, front-loaded sentence that directly states the action and target. Every word contributes meaning with 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?

The tool is simple with one optional parameter, but no output schema exists. The description does not hint at the structure of the returned list (e.g., process IDs, memory usage) or error scenarios, leaving a minor completeness gap.

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 schema fully documents the single 'format' parameter with enum values and a default, giving it 100% schema coverage. The description adds no extra meaning about the parameter, so the baseline of 3 is appropriate.

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?

Description uses a specific verb 'List' and a precise resource 'processes currently using NVIDIA GPU VRAM', making it clear what the tool does. It also distinguishes itself from sibling tools like gpu_status, which likely reports overall GPU health rather than per-process VRAM usage.

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 context is only implied by the description ('List processes...') with no explicit guidance on when to choose this tool over alternatives such as gpu_status or top_processes. There are no exclusion criteria or references to sibling tools.

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