get_stock_fundamental

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

With no annotations provided, the description carries the full burden. It clearly indicates this is a read operation ('retrieves'), shows the return format with a detailed example, and implies date-range functionality. However, it doesn't disclose potential limitations like rate limits, authentication requirements, data freshness, or error conditions that would be important for an agent.

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 with clear sections (purpose, Args, Returns, example). Every sentence earns its place, though the detailed example DataFrame takes significant space. The core information is front-loaded with the purpose statement first, making it easy to understand quickly.

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?

For a read-only tool with 3 parameters and no output schema, the description provides substantial context. It clearly explains what data is returned (fundamental metrics), shows the exact return format with a realistic example, and documents all parameters. The main gap is lack of behavioral constraints that would normally come from annotations.

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?

With 0% schema description coverage, the description fully compensates by providing clear parameter documentation in the Args section. It explains what each parameter represents (start date, end date, ticker symbol), shows the expected format (YYYYMMDD), and provides a concrete usage example that demonstrates all three parameters in action.

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 retrieves fundamental data (PER/PBR/Dividend Yield) for a specific stock, providing a specific verb ('retrieves') and resource ('fundamental data'). It distinguishes from siblings like get_stock_market_cap or get_stock_ohlcv by specifying the type of financial data, though it doesn't explicitly contrast with them.

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 like get_stock_market_cap or get_stock_ohlcv. It states what the tool does but offers no context about when it's appropriate or what problems it solves compared to sibling tools.

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