company_fundamentals

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only operation by listing data retrieval, but doesn't specify critical details like rate limits, authentication needs, data freshness, or error handling. For a tool with no annotations, this leaves significant behavioral gaps unaddressed.

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 efficiently structured with a clear purpose statement followed by parameter explanations. Both sentences earn their place by defining the tool's scope and clarifying parameter usage. However, the 'Args:' section formatting is slightly redundant with the parameter semantics explanation, preventing a perfect score.

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 (2 parameters, no annotations, but with output schema), the description is reasonably complete. It covers what data is returned and parameter usage. Since an output schema exists, the description doesn't need to detail return values. The main gap is lack of behavioral context, but the presence of output schema reduces the completeness burden.

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 description must compensate. It clearly explains that both 'ticker' and 'symbol' are aliases for stock ticker symbols, providing examples (AAPL, TSLA, MSFT) and clarifying they're interchangeable. This adds meaningful context beyond the bare schema, though it doesn't detail format constraints beyond examples.

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 provides 'full fundamental data' and lists specific metrics (revenue, earnings, P/E ratio, etc.), making the purpose evident. It distinguishes from sibling tools like 'stock_quote' by focusing on comprehensive fundamentals rather than just price data. However, it doesn't explicitly contrast with 'sec_filing' which might also provide fundamental data, preventing 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 like 'stock_quote' or 'sec_filing'. It mentions the parameters but doesn't explain scenarios where fundamental data is preferred over simpler quotes or detailed filings. This lack of comparative context leaves the agent without clear usage direction.

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