get_fair_market_rent

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

Beyond the readOnly and idempotent annotations, the description discloses that state-level queries return hundreds of records and that the output is monthly rent estimates by bedroom count. It also names the data source, adding useful context.

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 three sentences, each earning its place: purpose, caveat/guidance, and source. It is front-loaded with the primary action and resource, with no wasted words.

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?

Without an output schema, the description adequately covers the return type (monthly rent estimates by bedroom count) and the key operational caveat (state-level volume). Combined with the schema, it gives the agent sufficient context to use the tool 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?

The input schema fully describes all three parameters, including enum values and format notes, so the description adds no new parameter details. The mention of area types in the description only mirrors the schema.

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 it looks up HUD Fair Market Rent rates for a geographic area, specifying the resource and verb. It distinguishes from sibling tools like get_fmr_trend by focusing on rates rather than trends, and mentions output by bedroom count.

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 provides explicit guidance on area type selection: 'Use ZIP or county lookups when only a single area is needed' and warns that state-level queries return hundreds of records. It doesn't name alternative tools, but the area-type guidance is clear and actionable.

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