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

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds valuable context by specifying the aggregated nature of the data, the return fields, and the time-range/interval options, which go beyond what annotations alone convey.

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, front-loaded sentence with example queries, followed by a concise explanation of the output and use case. Every clause earns its place, with no redundancy or fluff.

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 read-only market trends tool with complete schema coverage and an output schema, the description covers purpose, usage context, and return type sufficiently. It does not dwell on edge cases or limitations, but these are less critical given the annotations and output schema.

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 coverage is 100%, so the baseline is 3. The description mentions the date range and intervals in prose, mirroring the schema's param descriptions but not adding new semantic depth beyond what is already present in the input 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 the tool provides aggregated real estate market trends by ZIP, listing the specific outputs (average/median sale price, sales volume, price changes) and time intervals. It distinguishes itself from sibling tools like attom_sales_history and attom_property_detail by emphasizing aggregate market-level data rather than individual addresses.

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 gives concrete example queries and explicitly advises using it for market-direction questions 'before pulling individual addresses,' which implies a distinction from address-level tools. However, it does not explicitly name alternative sibling tools or provide exclusion conditions beyond the address-level contrast.

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