get_stock_monthly_trading

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 returns monthly trading information and lists the fields, but does not describe behavioral traits such as rate limits, error handling, authentication requirements, or whether the data is real-time or historical. For a read operation with no annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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: the first sentence states the purpose clearly, followed by a bulleted list of return fields. Every sentence earns its place, with no redundant or verbose language. It is appropriately sized for the tool's complexity.

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 simplicity (one parameter, no annotations, but with an output schema implied by the return fields listed), the description is mostly complete. It explains what the tool does and what it returns, though it lacks behavioral context and usage guidelines. The presence of detailed return information compensates for the lack of an explicit output schema, making it adequate for basic understanding.

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 input schema has 0% description coverage, but the description compensates by specifying that the parameter 'code' is a 'stock code' for a 'listed company stock'. This adds meaningful context beyond the schema's minimal title ('Code'), clarifying the parameter's purpose and format. Since there is only one parameter, the description effectively covers its semantics.

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 specific action ('Obtain monthly trading information') and resource ('for a listed company stock based on its stock code'), distinguishing it from siblings like get_stock_daily_trading or get_stock_yearly_trading by specifying the monthly timeframe. It provides a concrete verb+resource combination that is unambiguous.

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 does not mention any prerequisites, constraints, or comparisons to sibling tools (e.g., get_stock_daily_trading for daily data or get_stock_yearly_trading for yearly data). The agent must infer usage from the name and description alone without explicit direction.

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