calculate_student_loan_repayment

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

No annotations provided, so description must cover behavioral traits. It states the tool computes and returns values, but it does not disclose potential side effects, permissions, or error conditions. Additionally, the description incorrectly mentions 'term years' as input while the schema uses 'monthly_payment', creating confusion.

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 concise (two sentences plus a note) and front-loaded, but it includes an inaccurate input list and an off-topic reference to list_bundles.

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 that the tool has an output schema (not shown), the description mentions return values but fails to clarify the relationship between inputs (e.g., monthly_payment vs term years). The inconsistency with the schema leaves gaps for the 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?

Schema coverage is 100% with descriptions for all parameters, but the description adds inaccurate information: it lists 'term years' as an input instead of 'monthly_payment'. This misalignment reduces the value added beyond the schema.

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 it computes student loan repayment schedule and total interest, with a specific use case for graduates. However, it does not differentiate from sibling tools like 'calculate_loan_payment' or 'calculate_loan_early_repayment'.

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?

It provides a usage context ('use for graduates planning repayment') but does not specify when not to use the tool or suggest alternatives. The reference to list_bundles is vague.

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