add_term

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It mentions that term_name must be unique and that the return is a JSON object, but it does not describe what happens on duplicate terms, whether the vocabulary must already exist, or any side effects. This leaves significant behavioral uncertainty.

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-organized into Name, Args, Returns, and Example sections. It is concise, with each section adding necessary information and no redundancy. The example is particularly useful for illustrating expected argument usage.

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 tool's simplicity, the description is fairly complete: it explains purpose, parameters, return format, and shows an example. However, it omits the prerequisite that the target vocabulary must already exist and does not cover error conditions, which are important for an agent to use the tool without failures.

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 input schema has no descriptions (0% coverage), so the description must compensate. It does so thoroughly by explaining each parameter: vocabulary_name with an example, term_name with uniqueness note, description, and synonyms. This fully covers the meaning of all four parameters.

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 'Add a new term to a vocabulary,' which is a specific verb-resource pair. This distinguishes it from sibling tools like add_synonym (which adds synonyms to existing terms) and create_vocabulary (which creates the vocabulary itself). The example further clarifies the intended operation.

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 through its example and purpose, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives. The agent must infer that this tool is for creating new terms rather than modifying existing ones.

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