get_company_eps_statistics

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

No annotations are provided, so the description carries full burden. It mentions 'Obtain' which implies a read operation, but doesn't disclose behavioral traits like data freshness, rate limits, authentication needs, or what 'by industry' entails (e.g., comparison, ranking, or raw data). This leaves significant gaps for an agent to understand 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 a single, well-structured sentence that front-loads the core purpose ('Obtain EPS statistics by industry') and efficiently specifies the target ('for a listed company based on its stock code'). There's no wasted verbiage, making it highly concise and easy to parse.

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 moderate complexity (financial data retrieval), no annotations, and an output schema (which handles return values), the description is minimally adequate. It covers the basic purpose but lacks details on usage context, behavioral constraints, and parameter nuances, leaving the agent with incomplete guidance despite the output schema.

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 minimal meaning beyond the input schema. It clarifies that 'code' refers to a 'stock code' for a 'listed company', which provides context not in the schema (which has 0% description coverage). However, it doesn't explain format (e.g., ticker symbol), validation, or examples, leaving the parameter only partially documented.

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 action ('Obtain EPS statistics by industry') and target resource ('for a listed company based on its stock code'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_company_profitability_analysis' or 'get_stock_valuation_ratios' that might also provide financial metrics, 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. With many sibling tools offering company financial data (e.g., 'get_company_profitability_analysis', 'get_company_income_statement'), there's no indication of what makes EPS statistics by industry unique or when it's preferred over other tools.

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