colab_get_runtime

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

With no annotations, the description carries the behavioral burden. It does convey that the operation is a read-only status retrieval and enumerates the returned categories, but it does not mention potential side effects, error conditions, session handling, or whether information is returned for the active session only.

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 states the resource first and then enumerates the key result components without any filler. Every part adds useful information.

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 and its output components are listed, but there is no output schema and the optional session_id parameter is left completely unexplained. The description is adequate for a casual overview but not fully complete for an agent deciding how to invoke the 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?

Schema description coverage is 0%, and the description never mentions the session_id parameter. An agent cannot tell what session_id refers to, whether it is optional in practice, or what happens when it is omitted, so the description fails to compensate for the undocumented schema.

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') and a clear resource ('runtime status'), and then lists exactly what is included: active sessions, Python version, and CUDA/torch availability. This distinguishes it from sibling tools like colab_get_gpu or colab_get_cpu, which target individual resources.

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 description gives no guidance about when to use this tool versus alternatives such as colab_get_gpu, colab_get_cpu, or colab_get_memory. It does not state exclusions or point to a more specialized sibling for narrower queries.

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