check_runtime

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

No annotations are provided, so the description is the sole source of behavioral information. It implies a read-only operation (checks) but does not explicitly state it is safe or detail any side effects, permissions, or performance implications. It is minimally adequate.

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 sentence of 15 words, efficiently conveying the tool's purpose without redundancy. It is front-loaded with the action and resource.

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 the tool has no parameters, no output schema, and no annotations, the description provides a reasonably complete picture by enumerating the information checked (Python, platform, CPU, working directory, package versions). It lacks details on output format but is sufficient for a simple inspection 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 input schema has no parameters, so the description adds value by specifying what aspects of the runtime are checked. Without parameters, the baseline is 4, and the description fulfills that by clarifying the tool's output scope.

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 clearly states the tool checks current Colab runtime details including Python, platform, CPU, working directory, and package versions. It specifies a verb ('Checks') and resource ('current Colab runtime') and is distinct from siblings like 'check_gpu' or 'get_connection_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 description provides no guidance on when to use this tool versus alternatives like 'check_gpu' or 'resource_usage_snapshot'. It does not mention any prerequisites or context for usage.

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