get_banxico_reserves_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 states the tool 'Get[s]' data, implying a read-only operation, but doesn't clarify aspects like authentication needs, rate limits, data freshness, or error handling. For a data-fetching tool with zero annotation coverage, this leaves significant gaps in understanding its 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 concise, using clear sections ('Args:', 'Returns:') without unnecessary details. Every sentence adds value: the first states the purpose, and the subsequent lines explain parameters and returns efficiently. It's front-loaded with the core functionality, making it easy to scan and understand.

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, no nested objects) and the presence of an output schema (which handles return value documentation), the description is reasonably complete. It covers the purpose, parameter semantics, and return scope. However, the lack of usage guidelines and behavioral details (e.g., data source or update frequency) prevents a perfect score, as these could aid the agent in contextual decisions.

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 it as 'Maximum number of recent data points (default: 30).' This clarifies its purpose beyond the schema's technical definition. With 0% schema description coverage, the description fully compensates, providing essential semantic information that aids correct usage.

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 Banxico Reserve Assets data.' This specifies the verb ('Get') and resource ('Banxico Reserve Assets data'), making it immediately understandable. However, it doesn't differentiate this tool from its siblings (like get_cetes_28_data or get_inflation_data) beyond the specific data type, which prevents 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, context for selecting reserve assets data over other economic indicators, or any prerequisites. The agent must infer usage from the tool name alone, which is insufficient for effective decision-making.

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