company_trend

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does disclose the year range (2019-2025) and the stock code format, which adds context. However, it does not describe the output structure, error behavior, or any access/rate limits. Since it's a simple read-only query tool, the description provides adequate but minimal behavioral context.

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: the main purpose is in the first sentence, followed by a clearly formatted Args section. Every sentence provides necessary information without redundancy. It is appropriately sized for a simple single-parameter tool.

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?

The tool has one parameter, no annotations, and an output schema. The description covers the purpose and the parameter format, which is sufficient for the tool's simplicity. The presence of an output schema means return value details are documented elsewhere. A minor gap is the lack of explicit guidance on what the output looks like (e.g., a table or list), but it is not necessary. Overall, the description is nearly complete for this context.

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 schema description coverage is 0%, and the schema only lists 'code' as a string with no meaning. The description compensates fully by explaining that the parameter is a 4-6 digit TWSE/TPEx stock code and provides an example ('2330'). This is essential and adds complete semantic value beyond the schema.

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 shows one company's median pay for each year in a specific range (2019-2025). This uses a specific verb ('show') and a resource ('one company's median pay'), and the year range adds specificity. The sibling tools (lookup_company, industry_stats, top_by_median) appear to serve different purposes, so this description effectively distinguishes the tool.

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 implies the use case: to retrieve annual median pay data for a single company. It provides a clear context for when the tool is appropriate but does not explicitly contrast it with sibling tools or state exclusions. Since it gives a focused purpose, it is above the 'implied usage' level but lacks explicit alternatives.

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