APIbase

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 identifies Finnhub as the data source (useful attribution), but fails to disclose rate limits, caching behavior, data freshness, or error handling for invalid tickers.

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, efficient sentence using an em-dash to front-load the action and append the detailed field list. Every element serves a purpose with no wasted words.

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 simplicity (one required parameter, no output schema), the description adequately compensates by listing all major return fields. It could be improved by noting error conditions or data freshness, but it is sufficient for tool selection.

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 100% schema description coverage (the 'symbol' parameter is fully documented in the schema), the description meets the baseline expectation. It does not add additional parameter guidance (like ticker format requirements), but none is needed given the schema's example.

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 a 'Company profile by ticker' and explicitly enumerates the specific data fields returned (name, exchange, industry, market cap, etc.), distinguishing it from sibling tools like stocks.market.quote (prices) or stocks.company.news (news).

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?

While it lacks explicit 'when-not-to-use' statements, the detailed field list provides clear contextual guidance for selecting this tool over siblings (e.g., use this for fundamental company data like IPO date and industry, not for real-time prices or news).

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