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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds one useful behavioral fact beyond that: the return is 'static text' with no computation or state change. It does not say how long the text is or whether it references other tools.

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?

A single front-loaded sentence naming the subject, then a topic list, then a short modifier about output type. Dense but every clause maps to a real topic; the only soft spot is that the algorithm names are more than an agent strictly needs to pick the tool.

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 static-text tool with no output schema, the description gives enough: what subject it covers, what it does not do (no computation), and that it returns prose. No output-shape explanation is required since annotations and 'Static text.' already set expectations.

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 takes zero parameters, so the baseline is 4 and there is nothing about inputs the description could add. No parameter discussion is needed or 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?

The description states a specific resource and scope: a primer on greenfield analysis covering center-of-gravity (Weber) siting, Weiszfeld's algorithm, location-allocation, and service constraints. The closing 'Static text.' separates it from computational siblings like get_greenfield_result or list_greenfield_demos, though it never names those siblings directly.

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?

It explains a domain-level choice ('when to use greenfield versus facility selection'), which is content the primer covers rather than guidance on calling this tool. There is no explicit instruction such as 'read this before running greenfield analysis' and no routing against explain_optimization or explain_simulation.

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