get_area_demographics

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

No annotations exist, so the description carries the burden. It states the tool returns data from the US Census ACS, hinting at read-only behavior, but does not disclose other traits like authentication, rate limits, or data freshness. The behavioral disclosure is minimal.

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 concise and front-loaded: a single sentence on purpose, followed by a bullet list of data fields and an Args section. Every sentence adds value without redundancy.

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?

An output schema exists, reducing the need to explain return values, but the description still lists them. However, it omits details on default behavior when 'county' is omitted (state vs county level), error scenarios, or geographic scope constraints, leaving some completeness gaps.

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 compensates by describing the 'state' parameter as US name/abbreviation with examples, and the 'county' parameter as optional 3-digit FIPS code. This adds meaningful guidance beyond the schema's bare type and title.

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 retrieves demographic data for US states or counties, listing specific data fields (population, median income, etc.). It uses a specific verb ('get') and distinguishes from sibling tools that focus on cost of living, housing, or amenities.

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 does not provide guidance on when to use this tool versus alternatives like compare_areas or get_cost_of_living. It lacks explicit context for selection, leaving the agent to infer without comparative direction.

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