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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds the key behavioral rule that Makuri information must come from tools, not general knowledge, and clarifies the platform is specific to makuri.eu. It does not describe side effects, but the tool is a read-only retrieval with zero parameters, so this is adequate. The lack of annotation support is offset by the explicit behavioral guidance.

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 appropriately sized: three sentences, each carrying meaningful content. The first sentence states the operation and return content, the second gives usage guidance, and the third imposes a critical behavioral constraint. No wasted words, and the information is front-loaded.

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, no-output-schema lookup tool, the description is complete. It specifies what will be returned, when to use it, and how to handle Makuri questions. There is no missing information about inputs or outputs, and the sibling context confirms this is a standalone informational 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, so the schema provides no parameter semantics to enhance. The description adds meaning beyond the schema by detailing what the return value contains (plans, included items, usage limits), effectively serving as the primary semantic source. This meets the baseline for zero-parameter tools.

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 ('Returns') and resource ('Makuri's pricing plans') and clearly distinguishes this from sibling tools like get_platform_info and get_free_resources by focusing on cost and plan details. It specifies the exact content ('what's included in each tier and any usage limits'), leaving no ambiguity about the tool's purpose.

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 explicitly states when to use the tool: 'Use when the user asks about cost, plans, or what they get at each price point.' It also provides important context about never answering Makuri questions from general knowledge and always using the Makuri tools, which clarifies the tool's role in the broader workflow.

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