print_latex_tensor

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

No annotations are provided, so the description carries the full behavioral burden. 'Prints' implies a read-only operation, but the description does not explicitly state side-effect-free behavior, permissions, error handling, or what happens with an invalid key; it only adds that output is LaTeX.

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 with no filler or repetition. It states the action and output format efficiently.

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 has an output schema, so return-format detail is not required in the description. However, the missing parameter semantics and lack of sibling differentiation leave meaningful gaps for correct invocation.

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 single parameter tensor_key is undocumented in both the schema and description. The phrase 'stored tensor expression' only weakly hints that tensor_key identifies a stored tensor, but gives no format or source 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 uses a specific verb and resource: 'Prints' a 'stored tensor expression' in LaTeX format. It is clear what the tool does, but it does not differentiate itself from the sibling print_latex_expression.

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?

There is no guidance on when to use this tool versus alternatives such as print_latex_expression, nor any prerequisites or exclusions. The agent must infer usage entirely from the name and purpose.

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