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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds behavioral traits beyond that: it is 'deterministic' and uses 'same math as size_loan.' This clarifies output consistency and computational basis, which is valuable context not present in annotations. It does not describe return format or performance limits, but the deterministic note and math reference suffice for a strong score.

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 two sentences with the primary purpose front-loaded and a concise deterministic note at the end. It is efficient with no redundancy. It could be more structured (e.g., bullet points for modes), but it remains clear and readable.

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?

With 8 parameters (including nested objects), no output schema, and only a high-level description, the tool is not fully specified. The description does not explain what the output looks like (e.g., a table or list of scenarios), nor does it detail the required inputs or how the modes differ operationally. For a complex tool like this, an agent would need additional guidance on expected inputs and outputs to invoke it correctly.

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%—the description mentions no parameters at all. The schema itself provides types and ranges but no semantic meaning (e.g., what 'rates' or 'thresholds' represent). The description only hints at the mode parameter via the three scenario types but does not explain required inputs (netOperatingIncome, estimatedValue) or how thresholds and NOI deltas are used. With 0% coverage, the description fails to compensate, leaving agents to infer parameter purpose from names alone.

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 states the tool's purpose: running what-if loan sizing scenarios across assumptions (rate ladder, NOI sensitivity, loan feasibility). It explicitly distinguishes itself from size_loan by noting 'same math as size_loan, swept,' which differentiates it from the sibling tool. The verb 'Run' and resource 'loan sizing' are specific.

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 when to use this tool—when a range of assumptions is needed rather than a single calculation—by contrasting with size_loan. It names the alternative (size_loan) and notes the sweeping behavior, giving context for selection. However, it does not explicitly state when not to use it (e.g., for single-point calculations), which prevents a 5.

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