colab_get_gpu

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

With no annotations provided, the description carries the full burden. The verb 'Get' and the listing of informational fields imply a read-only operation, but the description does not cover edge cases like missing or invalid session_id, or whether an active runtime is required. It adds some useful context beyond the name but could be more explicit about expected behavior.

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 sentence that states the operation, target, and key output detail in a parenthetical. The content is front-loaded with the important resource name and there is no wasted wording.

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 simple getter with one parameter, no output schema, and no annotations, the description is mostly satisfactory: it names the resource, the returned fields, and the runtime scope. The primary omissions are optionality details and explicit alternative routing, but these are secondary for such a low-complexity tool.

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 sole parameter session_id has no schema description (0% coverage), so the description must compensate. 'or a runtime session' gives some context linking the parameter to a runtime, but it does not explain the format, where to get the session_id, or that it is optional (as indicated by required=0). This is a moderate compensation but not thorough.

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 uses a specific verb ('Get') with a clear resource ('GPU/VRAM info') and explicitly lists the returned fields (device name, memory, count). It is immediately distinguishable from sibling tools like colab_get_cpu and colab_get_memory.

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 'for a runtime session' indicates the tool's context of use, and the focus on GPU/VRAM clearly separates it from sibling resource-specific getters. However, it does not explicitly state when not to use it or name alternatives such as colab_get_cpu.

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