get_dividend_yield

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

No annotations are provided, so the description carries the full burden. It only states that it fetches data, implying a read operation, but does not disclose behavior such as default date ranges, handling of invalid tickers, rate limits, or output format. For a data retrieval tool without output schema, 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 a single, concise sentence that immediately states the action and resource. It contains no filler or redundant repetition of the tool name. Every word contributes to the meaning, making it appropriately sized and front-loaded.

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 absence of an output schema and annotations, the description should provide additional context about return values, date range handling, or potential caveats. It does none of this, leaving the agent uncertain about what data will be returned or how the optional parameters affect the output. The tool has moderate complexity (4 parameters, temporal filters), so this is a significant gap.

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 provides descriptions for all four parameters (ticker, columns, endDate, startDate), covering 100% of them. The description adds no extra semantic meaning beyond what the schema already provides, so the baseline score of 3 applies.

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 function: 'Fetches historical dividend yield data for a given ticker.' It uses a specific verb ('fetches') and a specific resource ('historical dividend yield data'), which distinguishes it from sibling tools like get_dividend_distributions (which deals with distributions) and get_fundamentals_daily_metrics (which covers other metrics).

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?

No guidance is provided regarding when to use this tool versus alternatives. It does not mention that this is for historical yield analysis, nor does it exclude use cases such as live yield or distribution data. There are no explicit alternatives or contextual cues beyond the name itself.

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