colab_get_package_version

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It does not mention potential errors (e.g., package not installed), whether a session is required, or whether the tool is read-only (though it likely is). The description adds minimal context beyond the name.

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 concise and front-loaded with the key action. It is a single sentence with no fluff, but it under-specifies rather than being overlong, so it earns a 4 for conciseness, but the lack of detail is penalized elsewhere.

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 that there is no output schema, no annotations, and 0% schema coverage, the description is incomplete. It does not specify what the response format is (e.g., string of version number) or any prerequisites (e.g., session must exist). For a tool that queries runtime state, an agent needs more context 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?

Schema description coverage is 0%, meaning the schema gives no descriptions for 'package' or 'session_id'. The description only mentions 'package' implicitly but not 'session_id'. It does not clarify the format of 'package' (e.g., PyPI name) or when 'session_id' is needed, so the description fails to compensate for the schema's lack of details.

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 verb 'Get' and the resource 'installed version of a specific package in the runtime', which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like colab_list_packages, but the action of getting a version is distinct enough that an agent can infer the difference.

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 does not provide any guidance on when to use this tool versus alternatives. For example, there is no mention of when to use colab_list_packages instead (e.g., if you need all packages) or whether this tool requires a session. The agent has to infer usage from the sibling names alone.

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