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tresor4k

macalc

calculate_us_student_loan

Calculate US student loan repayment under standard, graduated, or income-driven plans. Input loan balance and annual rate to determine monthly payments.

Instructions

Calculate US student loan repayment under standard, graduated, or income-driven plans. Returns: {loan_balance}. See list_bundles for related 'finance-us' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
loan_balanceYesOutstanding loan balance in USD
annual_rateYesAnnual interest rate in %
planNoRepayment planstandard
annual_incomeNoAnnual income (required for income_driven plan)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoComputed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.
Behavior2/5

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

No annotations provided, so description must disclose behavioral traits. It states it returns {loan_balance} but does not mention that the tool is read-only, whether it requires specific permissions, or what happens with invalid inputs. The description is minimal and does not adequately cover the tool's behavior beyond a basic return value.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with verb and resource. No unnecessary words. Efficient and clear. Ideal for agent consumption.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (context signals indicate is has one), the description doesn't need to detail return format. It covers the main purpose and links to related tools. However, it could mention that the income_driven plan requires annual_income (though that is in the schema). Overall, sufficiently complete for a calculator tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for all four parameters. The description adds that it calculates repayment and returns loan_balance, but doesn't provide additional meaning beyond what the schema already conveys. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it calculates US student loan repayment under specific plans (standard, graduated, income-driven). The verb 'Calculate' is specific, and it distinguishes from siblings like UK student loan calculators. Reference to list_bundles provides clear context for related tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Describes when to use (US student loan repayment) and points to list_bundles for related calculators. However, it lacks explicit guidance on when not to use this tool versus alternatives, or scenarios where other tools are more appropriate. Mostly clear but not fully comprehensive.

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

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