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

The description goes beyond simple calculation by referencing 'AER' and 'value after inflation'. This informs the agent about the tool's ability to handle complex financial metrics and contextualize the output, adding behavioral depth not present in the annotations or schema.

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 definition is front-loaded with a highly effective calculation example, allowing the agent to immediately understand the tool's utility before even parsing the input schema.

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 rich input schema, clear annotations (e.g., readOnlyHint), and the detailed illustrative example, the description provides all the necessary context for a comprehensive understanding of the tool's capability and application.

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?

Since schema coverage is 100%, the description acts as a 'proof of concept'. It demonstrates how multiple parameters (initial deposit, monthly contribution, rate, years) work together in a real-world scenario and how the 'inflation' parameter results in 'value after inflation', adding crucial semantic context.

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 immediately establishes the tool's purpose (calculating compound interest) and provides a concrete, realistic example of its application. This makes it distinctly clear what the tool achieves compared to simpler siblings like 'simple_interest_calculator'.

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 doesn't give formal exclusions (e.g., 'do not use for...'), the description sets a high bar by demonstrating complex, real-world usage involving monthly deposits, initial sums, and inflation. This strongly implies its suitability for detailed financial planning over basic calculators.

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