input_get_type

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

With no annotations provided, the description carries the behavioral transparency burden. 'Get' clearly indicates a read operation, and the possible return values are disclosed, but there is no explicit statement about side effects, error behavior, or assumptions like input_path needing to exist.

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 with no wasted words. It fronts the action and answer domain immediately, and every component contributes meaning.

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 one-parameter read tool with no output schema, the description is largely sufficient: it names the resource and the exact return set. The main gaps are explicit parameter semantics and error behavior, but the low complexity keeps the impact modest.

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 does not explain the input_path parameter. The parameter name is somewhat self-explanatory and aligns with 'the Input dataset', but the description adds no explicit meaning about what value to pass or how it is used.

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 states a specific verb ('Get'), a specific resource ('the Input dataset type'), and enumerates the exact possible result values ('M', 'S', 'B'). This makes the purpose immediately clear and distinguishes it from sibling tools like input_get_field or input_get_data.

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?

No guidance is given about when to call this tool versus alternatives such as input_M, input_S, or input_B. The description implies its use when a type string is needed, but it does not state any exclusions or contextual conditions.

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