create_glossary

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

The description explains the creation action and lists parameters, but does not disclose potential errors, prerequisites (e.g., domain must exist), or side effects. With no annotations, the description carries full burden and provides only basic behavioral information. No contradictions.

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 structured with clear sections (Args, Returns, Example) and is concise. The example adds practical value. However, the opening sentence is slightly redundant with the Args section that follows.

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 absence of an output schema and annotations, the description covers all parameters and returns a generic 'API response'. It lacks details on error conditions, edge cases, or prerequisite checks (e.g., domain existence), which would be needed for full completeness.

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 has 0% description coverage, but the description's Args section adds meaningful context for each parameter (e.g., 'The ID of the domain where the glossary will be created'). This compensates well, though details like character limits are provided inconsistently (only for name and description).

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?

Clearly states 'Creates a new business glossary in Amazon DataZone.' The verb is specific ('creates'), the resource is defined ('business glossary'), and the platform is named, differentiating from siblings like create_glossary_term which creates a term within a glossary.

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 explicit guidelines on when to use this tool versus alternatives, such as when a glossary should be created before terms. The context is implied by the sibling tools (e.g., create_glossary_term), but no direct 'when to use' or 'when not to use' guidance is given.

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