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

With no annotations provided, the description carries full burden. It discloses output format (ASCII table), error behavior (returns error message for invalid ticker), and default value for days parameter. However, it doesn't mention rate limits, authentication needs, data source limitations, or pagination behavior.

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 well-organized Args and Returns sections. Every sentence adds value: the first states what the tool does, the Args explain parameters with examples, and the Returns specifies output format and error behavior.

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 has output schema), the description is quite complete. It covers purpose, parameters, output format, and error handling. The output schema exists, so the description appropriately doesn't need to detail return structure. Minor gaps include lack of rate limit or data freshness information.

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 description adds significant value beyond the schema (0% coverage). It explains that 'ticker' is a stock symbol with an example ('COIN' for Coinbase), clarifies that 'days' is optional with default 30, and specifies what the parameters control (historical data range). This fully compensates for the lack of schema descriptions.

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 specific action ('Fetch historical stock prices'), resource ('for the given ticker'), and output format ('in a table format'). It distinguishes from siblings like 'get_stock_price' (likely current price) and 'get_stock_list' (likely list of stocks).

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 'historical' data and table format, but doesn't explicitly state when to use this tool versus alternatives like 'get_stock_price' (which might provide current or real-time data). It provides clear default behavior for optional parameters.

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 carries the full burden of behavioral disclosure. It states the tool returns a list in an ASCII table format, which is useful, but lacks details on potential behaviors like rate limits, data freshness, error handling, or authentication needs. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it operates.

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 highly concise and well-structured: two brief sentences that directly state the tool's purpose and output format without any wasted words. It's front-loaded with the main action and efficiently conveys essential 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?

Given the tool's low complexity (0 parameters, simple output) and the presence of an output schema (which handles return value documentation), the description is reasonably complete. It covers the purpose and output format, though it could benefit from more behavioral context or usage guidelines to fully guide an agent.

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 has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't add parameter details, but since there are no parameters, this is acceptable. The baseline for 0 parameters is 4, as the description needn't compensate for missing param info.

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: 'Return a list of available crypto-related stocks in a table format.' It specifies the verb ('return'), resource ('crypto-related stocks'), and output format ('table format'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'get_historical_prices' or 'get_stock_price', which focus on price data rather than listing stocks.

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. It doesn't mention sibling tools or contexts where this tool is preferred, such as for initial discovery of crypto stocks before fetching prices. Without any usage context or exclusions, the agent must infer usage based on tool names alone.

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?

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool returns data in an ASCII table format, includes specific fields (ticker, company name, current price, timestamp), and handles errors for invalid tickers. However, it lacks details on rate limits, authentication needs, or data sources, which are relevant for a real-time financial tool.

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 well-structured and front-loaded with the core purpose, followed by clear sections for Args and Returns. Every sentence adds value: the first states what the tool does, the second explains the parameter, and the third details the return format and error handling. 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 low complexity (1 parameter, no nested objects) and the presence of an output schema (implied by the Returns section), the description is mostly complete. It covers the purpose, parameter meaning, and return format. However, for a real-time financial tool, additional context like data freshness or limitations would enhance completeness, but the output schema reduces the need for return value explanations.

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 description coverage is 0%, so the description must compensate. It adds meaningful semantics by explaining the 'ticker' parameter as a stock ticker symbol with an example ('COIN' for Coinbase), which clarifies usage beyond the bare schema. Since there's only one parameter, this is sufficient for a high score, though it doesn't cover edge cases like formatting requirements.

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 specific action ('Get real-time price'), the resource ('specific stock'), and the output format ('in a table format'). It distinguishes from sibling tools like 'get_historical_prices' by specifying 'real-time' and from 'get_stock_list' by focusing on a single stock rather than a list.

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 'real-time' price, suggesting it's for current data rather than historical (contrasting with 'get_historical_prices'). However, it doesn't explicitly state when NOT to use this tool or name alternatives, leaving some guidance implicit rather than explicit.

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