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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds useful context beyond them: the SEC loan-data provenance, the historical window, and that figures are aggregate medians/percentiles rather than individual loans.

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 that names the data and source before the metric list. It is dense—the metric list is long—but every clause carries information, with no filler.

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 only one optional parameter and no output schema, the description carries the burden of describing returns, and it enumerates the return metrics thoroughly. It stops short of describing result shape (e.g., how percentiles are presented, sample counts), which leaves a small gap.

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?

One optional parameter with 100% schema description coverage and a full enum, so the schema already does the work. The description's 'overall or for one property type' merely restates the omit-for-all behavior the schema documents; no extra syntax or filtering nuance is added.

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 concretely what the tool returns (underwritten loan size, LTV, DSCR, debt yield, occupancy medians/percentiles, IO share, term mix) and the data source and window (SEC loan data, last 12 months). This clearly distinguishes it from siblings like get_cmbs_rates, get_cmbs_maturity_wall and size_cmbs_loan, which cover different resources.

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 'what lenders actually underwrote' framing plus the trailing-12-month window tells the agent this is for observed market benchmark data, not forward-looking quoting or single-loan sizing. It never names an alternative tool or an exclusion, so routing is implied rather than explicit.

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