get_us_financials

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It does not mention rate limits, authorization needs, error handling, or what happens if an invalid ticker is given. Only the metrics returned are listed.

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 concise and well-structured: a one-line summary, example queries, a bullet list of returned metrics, and a parameter description. Every sentence earns its place without redundancy.

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 has one parameter and an output schema, the description lists the returned metrics, which is helpful. It is mostly complete but could mention if ticker must be a valid stock or any constraints on the input.

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 coverage is 0%, but the description adds meaning by specifying the parameter is a US ticker with an example ('AAPL'). This goes beyond the schema's minimal definition.

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 it returns US stock financials and valuation ratios (PER, PBR, etc.), with example queries like 'AAPL PER'. This distinguishes it from sibling tools focused on price, charts, or filings.

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?

It provides example queries that indicate when to use (e.g., valuation questions), but does not explicitly state when not to use or suggest alternatives. The context is clear enough for an AI agent to infer usage.

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