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

With no annotations, the description carries the full behavioral burden. It discloses that the response mirrors the public endpoint and explicitly excludes provider configuration identifiers and payment credentials, which is valuable context about what the tool will and will not return.

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 followed by a precise exclusion note. Every word earns its place; there is no redundant phrasing or unnecessary detail.

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 zero-parameter, public-catalog lookup, the description covers the purpose and the key exclusion. It does not spell out output format or authentication, but the simplicity of the tool and the 'public' qualifier make those omissions acceptable.

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 schema confirms this with an empty object. The description adds no parameter-specific detail, but none is needed; the baseline for a zero-parameter tool is appropriately high.

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 ('Return') plus a clear resource ('public plan catalog') and even ties it to an endpoint. It is distinct from the sibling tools, which target capabilities and AI web readiness, so an agent can immediately tell this is the pricing tool.

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 that this tool is for retrieving public pricing data but does not explicitly state when to use it over the siblings. There is no direct mention of alternatives or exclusions, though the tool name and endpoint reference make the intent reasonably clear.

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