get_public_company_balance_sheet

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 adds some behavioral context: 'Automatically detects company industry and uses appropriate financial statement format.' This explains adaptive formatting, which is useful. However, it lacks details on permissions, rate limits, data freshness, or error handling, leaving gaps for a tool that likely accesses financial data.

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 two sentences, front-loaded with the core purpose and followed by an additional behavioral detail. Every sentence adds value without redundancy, making it efficient and well-structured for quick understanding.

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 (single parameter, no annotations, but with an output schema), the description is reasonably complete. It covers the purpose, input semantics, and a key behavioral trait (automatic format detection). The output schema likely handles return values, so the description doesn't need to explain them. However, it could benefit from more context on limitations or sibling tool differentiation.

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?

Schema description coverage is 0%, so the schema provides no parameter details. The description adds meaning by specifying that the 'code' parameter is a 'stock code' for a 'public company', which clarifies its purpose beyond the generic schema. However, it does not explain format (e.g., ticker symbol conventions) or constraints, partially compensating but not fully.

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 purpose: 'Obtain balance sheet for a public company based on its stock code.' It specifies the verb ('obtain'), resource ('balance sheet'), and key input ('stock code'). However, it does not explicitly differentiate from sibling tools like 'get_company_balance_sheet', which might target non-public companies or have different scopes, leaving some ambiguity.

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 usage context by specifying 'public company' and 'stock code', suggesting it's for publicly traded entities. It does not provide explicit when-to-use guidance versus alternatives (e.g., 'get_company_balance_sheet' or other financial tools) or mention prerequisites like data availability or time periods, relying on implied understanding.

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