get_unemployment_data

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 the tool returns 'Current and historical unemployment rate data,' which implies a read-only operation, but doesn't cover critical aspects like rate limits, authentication needs, data freshness, or error handling. For a data-fetching tool with zero annotation coverage, this is insufficient.

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 with the core purpose, followed by clear sections for Args and Returns. It's concise with no wasted sentences, though the 'Returns' section is somewhat redundant given the output schema, slightly reducing efficiency.

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 low complexity (1 parameter) and the presence of an output schema, the description is minimally adequate. It covers the purpose and parameter semantics but lacks behavioral details and usage guidelines. Without annotations, it should do more to explain data scope or limitations, making it just sufficient but not comprehensive.

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 context for the single parameter 'limit' by explaining its default value (24) and purpose ('2 years of monthly data'), which goes beyond the input schema's basic type and default. With 0% schema description coverage, this compensation is effective, though it could detail format or constraints more.

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 unemployment rate data from Banxico.' It specifies the verb ('Get'), resource ('unemployment rate data'), and source ('Banxico'). However, it doesn't explicitly differentiate from sibling tools like 'get_inflation_data' or 'get_usd_mxn_historical_data' beyond the data type, which keeps it from a perfect score.

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 sibling tools or contexts where other tools might be more appropriate, such as using 'get_inflation_data' for inflation metrics or 'get_date_range_data' for broader queries. This leaves the agent without clear usage instructions.

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