get_housing_stats

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions what data is returned (median values, rent, vacancy rates) but lacks critical details: it doesn't specify data sources, timeframes, update frequency, rate limits, or error handling. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior.

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 well-structured and front-loaded, starting with the core purpose. It uses bullet points for 'Args' and 'Returns' to organize information efficiently, with no redundant sentences. Every part adds value, making it easy for an agent to parse quickly.

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?

Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is partially complete. It covers parameters and return types adequately, but lacks context on data sources, limitations, or sibling tool differentiation. The output schema likely details the return structure, so the description doesn't need to explain return values, but overall completeness is limited by missing behavioral and usage details.

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 description adds meaningful semantics beyond the input schema, which has 0% description coverage. It explains that 'state' is a 'Two-letter state code (e.g., 'CA', 'TX')' and 'county' is an 'Optional county FIPS code (3 digits)', clarifying format and examples not present in the schema. However, it doesn't detail validation rules or provide a full list of valid codes, leaving some ambiguity.

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: 'Get housing statistics for a US state or county.' It specifies the verb ('Get') and resource ('housing statistics'), and distinguishes it from siblings by focusing on US housing data. However, it doesn't explicitly differentiate from similar tools like 'get_demographics' or 'query_census', which might also provide related data.

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 no guidance on when to use this tool versus alternatives. It doesn't mention siblings like 'get_demographics' or 'query_census', which could offer overlapping or complementary data. There's no context on prerequisites, such as data availability or limitations, leaving the agent to infer usage based on the tool name alone.

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