update_term_description

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

No annotations are provided, so the description must carry the full burden. It states that the tool updates the description and returns a JSON object with status, name, and updated description, but it does not disclose potential errors, requirements for the term existing, or side effects like overwriting. The example adds some clarity but not deep behavioral detail.

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 well-structured with a one-line summary, labeled args, returns, and an example. It is moderately sized but every part contributes to understanding, and the front-loaded summary allows quick comprehension.

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 3-parameter update without annotations, the description covers all key aspects: what it does, the parameters, the return format, and an example. It lacks details on error handling and prerequisites, but the presence of an output schema mitigates the need for return-value description. Overall, it is nearly complete for this complexity level.

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 no descriptions for the three string parameters, but the description explains each one: vocabulary_name as the vocabulary table name, term_name as the primary term name, and description as the new text. It also gives a concrete example showing the expected values, substantially adding meaning beyond the schema.

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 opens with a clear verb+object: 'Update the description of a vocabulary term.' This precisely identifies the target resource (a term within a vocabulary table) and distinguishes it from sibling tools that set descriptions on datasets, tables, or columns. The example further reinforces the intent.

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 use for updating term descriptions but does not explicitly state when to use it versus alternatives like set_dataset_description or set_column_description. No exclusions or alternative recommendations are provided, leaving the agent to infer from the resource name.

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