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

No annotations are provided, so the description carries the full burden of disclosing behavior. It only states that the tool retrieves fundamental data, with no detail on return format, potential errors, rate limits, or how the 'metrics' parameter affects the response. This is a minimal disclosure without notable behavioral context.

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, concise sentence that front-loads the core purpose. It contains no fluff or redundant phrasing, making it easy to parse quickly.

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?

With no output schema and no annotations, the description does not adequately explain what the tool returns or how the various metrics behave. The schema lists valid metrics but the description does not connect these to the data source or provide enough context for an agent to confidently predict the tool's full behavior.

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 input schema fully covers both parameters (symbol and metrics), including descriptions and an enum for metrics. With high schema coverage, the description need not add much; it adds no parameter-level meaning beyond the schema, so a baseline score of 3 is appropriate.

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 uses a specific verb ('Get') and a clear resource ('company fundamental data'), which precisely conveys the tool's function. It also distinguishes from the sibling tool 'stock_price' by focusing on fundamentals rather than price.

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 referencing 'fundamental data', which naturally separates it from price-related queries. However, it does not explicitly state when to use this tool over alternatives, nor does it mention any exclusions or prerequisites.

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

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. While 'Get' implies a read-only operation and 'real-time and historical' conveys the time scope, it does not mention Alpha Vantage rate limits, API key requirements, or the structure of the returned data. This leaves important behavioral traits undisclosed.

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 sentence that is front-loaded with the main purpose and includes the data source. Every word earns its place, and there is no unnecessary repetition of schema information.

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?

The tool has four parameters and no output schema, so the description should ideally clarify what the response looks like or mention that it returns a time series. The description only states 'price data' without explaining the response format, default intervals, or behavior of outputSize. It is adequate but leaves gaps.

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 schema provides 100% coverage for all four parameters, including descriptions and enums for dataType, interval, and outputSize. The description adds no parameter-specific information, so the baseline score of 3 applies; the schema handles the semantic burden.

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 uses the specific verb 'Get' and identifies the resource as 'real-time and historical stock price data from Alpha Vantage.' It clearly distinguishes this tool from the sibling 'company_fundamentals' by focusing on price data rather than fundamentals.

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 gives clear context: use this tool when you need real-time or historical stock price data from Alpha Vantage. It does not explicitly name an alternative or provide when-not-to-use guidance, but the contrast with company_fundamentals is implied, and no exclusions are stated.

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