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

Despite no annotations, the description discloses side effects (quote only, no execution, no credits consumed), temporal validity (15 min), pricing behavior (binding USD price), and auth header requirements. This gives the agent a realistic model of calling the tool.

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?

Front-loaded with purpose, then output/behavior, follow-up workflow, and auth. Every sentence adds needed context, but the minor grammar issue ('regions Returns') prevents a perfect structure score.

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?

Complete for a zero-parameter quote tool: it states what is returned, the quote validity, that no execution occurs, the follow-up via execute_quote, and the required auth. Even without an output schema, an agent knows the key return values.

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 is empty, so the 0-parameter baseline applies and there is little for the description to add. The description does not invent parameters or explain additionalProperties, but none are expected.

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?

States a specific action ('Request a ... quote') and a specific product ('Crop Yield Forecast') with satellite-derived context, making it distinct from the many other quote_* siblings. It also names the output (price and quote_id), so an agent knows exactly what the tool is for.

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?

Explicitly defines the workflow: call this tool to obtain a quote, then use execute_quote with the quote_id to run the forecast and consume credits. It also says when not to use it ('no execution yet'), names the alternative sibling, and includes the API-key prerequisite.

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