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Calculate Student Loan Repayment

calculate_student_loan_repayment
Read-onlyIdempotent

Compute student loan repayment schedule and total interest. Use for graduates planning repayment. Inputs: loan amount, interest rate %, term years. Returns monthly payment, total paid, total interest. See list_bundles for related 'education' calculators.

Input Schema

NameRequiredDescriptionDefault
annual_rateYesAnnual interest rate percent
loan_amountYesLoan amount EUR
monthly_paymentYesMonthly payment EUR

Output 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).
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare this a safe, idempotent, non-destructive read, so the safety burden is covered. The description's added behavioral claim is inaccurate: it says the tool 'Returns monthly payment' when monthly_payment is in fact a required input, which will actively mislead an agent about the tool's behavior.

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

Conciseness4/5

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

Four short sentences, purpose front-loaded, no filler. It spends a sentence on return values that an existing output schema already provides, which is mild redundancy rather than bloat.

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

Completeness2/5

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

For a read-only calculator with a full output schema, the description should be complete and consistent with the schema. Instead it inventories the wrong inputs and misidentifies a required input as a return value, so an agent cannot rely on it to construct a valid call.

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

Parameters2/5

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

Schema coverage is 100%, so the schema documents all three parameters correctly. The description contradicts it by listing inputs as 'loan amount, interest rate %, term years' — term years does not exist and monthly_payment EUR is never mentioned. This is worse than adding nothing.

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

Purpose4/5

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

States a specific verb and resource ('Compute student loan repayment schedule and total interest') and adds a use-case anchor ('graduates planning repayment'). However, it never distinguishes itself from the near-identical siblings calculate_uk_student_loan and calculate_us_student_loan, leaving the agent to guess which one applies.

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

Usage Guidelines3/5

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

'Use for graduates planning repayment' implies a scenario but gives no explicit when/when-not or alternative-selection rule. The pointer to list_bundles routes to a catalog tool rather than naming the competing student-loan calculators, so the routing value is weak.

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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