get_model_variable

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

No annotations are provided, so the description carries the full burden. It mentions 'Full metadata' but does not specify what that includes (e.g., dimensions, attributes). There is a potential ambiguity: the description says 'by netCDF name or kVARS member' but the schema only has a single 'name' parameter, which may accept both. No mention of side effects, permissions, or whether the operation is read-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 sentence that is concise and front-loaded with the primary purpose. Every word adds value with no waste.

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 lack of output schema and the complexity of returning metadata for a model variable, the description is insufficient. It does not describe the return value structure (e.g., dimensions, attributes, units). The parameter description is helpful but not exhaustive. Siblings like list_model_variables provide contrast but the tool's completeness is lacking.

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 provides only the parameter name 'Name' with no description. The tool's description adds significant meaning by clarifying that the parameter accepts a netCDF name or kVARS member. This compensates for the 0% schema description coverage, though it does not specify format constraints like case sensitivity or exact matching.

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 retrieves full metadata for a model variable, specifying the identifier by netCDF name or kVARS member. This distinguishes it from siblings like list_model_variables (listing) and search_model_variables (search).

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 implies usage when full metadata for a specific variable is needed, but does not explicitly state when to use or not use this tool versus alternatives like list_model_variables or search_model_variables. No guidance on prerequisites or context is given.

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