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

With no annotations, the description carries the full transparency burden. It states the output is 'machine-readable' but does not disclose format details, whether it returns all products at once, or if any authentication is needed. For a read-only parameterless operation, the description provides basic transparency but lacks richer behavioral context.

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, well-structured sentence that front-loads the core purpose and then lists the specific data included. Every word contributes value with no redundancy or filler. It is concise while remaining informative.

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 parameterless tool with no output schema, the description is largely complete: it states the scope ('all Dataplex products') and enumerates the return fields. Minor gaps remain, such as the exact data format or whether prices are in a particular currency, but these are not critical for a simple pricing lookup. The description covers the essential context needed for an agent to select and invoke the tool.

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 tool has zero parameters, and the input schema is empty, so there are no parameter semantics to explain. The baseline for 0 params is 4, and the description adds relevant context about the output content, which is sufficient. No additional parameter documentation is needed.

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 specifies the tool's purpose: retrieving machine-readable pricing for Dataplex products. It enumerates the specific data returned (monthly price, free-trial link, marketplace URL), which distinguishes it from sibling tools like get_product_details or get_sample_data. The verb is implied but the resource and scope are explicit.

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 provides no guidance on when to use this tool versus alternatives such as get_product_details or list_products. There is no mention of prerequisites, exclusions, or preferred use cases. The only usage signal is the tool name and the description's focus on pricing, which is implicit rather than explicit.

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