internal_rate_of_return

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

No annotations are provided, so the description carries full burden. It states the tool calculates IRR but doesn't disclose behavioral traits such as numerical method used (e.g., Newton's method), convergence behavior, error handling, or output format. For a financial calculation tool with 5 parameters, this is a significant gap in transparency.

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 in Chinese that directly states the tool's purpose. It's front-loaded with no wasted words, making it highly concise and well-structured for its minimal content.

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 complexity (financial calculation with 5 parameters), lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't provide enough context for an AI agent to understand how to use the tool effectively, missing details on behavior, parameters, and output.

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 description coverage is 0%, so parameters are undocumented in the schema. The description doesn't add any parameter semantics—it doesn't explain what 'initial_investment', 'cash_flows', 'initial_guess', 'tolerance', or 'max_iterations' mean or how they affect the calculation. This fails to compensate for the low schema coverage.

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: '计算投资项目的内部收益率（IRR）' translates to 'Calculate the internal rate of return (IRR) of an investment project.' It specifies the verb (calculate) and resource (IRR), but doesn't distinguish it from siblings like 'net_present_value' or 'future_value_annuity' that also perform financial calculations.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or comparisons to sibling tools like 'net_present_value' or 'bisection_method' (which might be related algorithms). Usage is implied only by the tool's name and purpose.

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