get_profit_data

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

No annotations are provided, so the description carries full burden. It mentions the return format ('Markdown table with profitability data or an error message'), which is helpful. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, rate limits, authentication requirements, data freshness, or what specific profitability metrics are included beyond the examples.

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 appropriately sized. It begins with the core purpose, then clearly documents parameters with examples, and ends with return information. Every sentence earns its place with no redundant 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 has 3 parameters with no schema descriptions and no annotations, the description does a good job explaining parameters and return format. However, for a data-fetching tool with many similar siblings, it should provide more context about when to use it versus alternatives and what specific data it returns. The existence of an output schema helps, but the description could better prepare the agent for proper usage.

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 0% schema description coverage, the description fully compensates by providing clear semantics for all 3 parameters: 'code' (stock code with example), 'year' (4-digit year with example), and 'quarter' (quarter number with valid values). This adds significant value beyond the bare schema, which only provides titles and types.

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: 'Fetches quarterly profitability data (e.g., ROE, net profit margin) for a stock.' It specifies the verb ('fetches'), resource ('quarterly profitability data'), and provides examples of metrics. However, it doesn't explicitly differentiate from sibling tools like 'get_hk_profit_data' or 'get_balance_data', which likely fetch different types of financial data.

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. With many sibling tools fetching different financial data types (balance, cash flow, growth, etc.), there's no indication of when profitability data is appropriate versus other metrics, nor any prerequisites or exclusions mentioned.

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