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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description does not need to state safety. It adds context about data sources (NAHB, ULI, industry composite) and the specific metrics returned, which is useful behavioral transparency beyond annotations. However, it does not describe return format or any limitations.

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, focused sentence that front-loads the core purpose and then adds target users and sources. Every clause adds value without redundancy, making it appropriately concise and well-structured.

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?

The tool is simple with only 2 parameters and no output schema, so the description provides sufficient context for most use cases: it lists the metrics, target audience, and sources. It does not discuss market_tier selection or output details, but for a benchmark lookup tool, the description is reasonably complete.

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?

Schema description coverage is 0%, so the description must compensate for parameter meanings. It mentions 'by product type' but does not elaborate on allowed values, and it completely omits the market_tier parameter. The enum values in the schema are self-explanatory, but the description fails to clarify how to combine them or what each parameter represents in the context of development benchmarks.

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 identifies the tool as providing development pro forma benchmarks including yield on cost, profit-on-cost, construction-to-perm spread, and return hurdles by product type. It specifies the resource (development benchmarks) and the verb (get) implicitly, and distinguishes from sibling tools by focusing on development-specific metrics.

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 states the intended users and scenarios: 'For developers underwriting new projects and lenders sizing construction loans.' This gives clear context on when to use the tool, though it does not explicitly mention when not to use it or name alternative tools. Still, the audience and purpose are well-defined.

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