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MaCalculatriceEnLigne

Calculate UK Student Loan

calculate_uk_student_loan
Read-onlyIdempotent

Calculate UK student loan repayments based on plan type and salary. Returns: {annual_salary, repayment_rate_pct, annual_repayment, monthly_repayment}. See list_bundles for related 'finance-uk' calculators.

Input Schema

NameRequiredDescriptionDefault
planNoStudent loan plan: 1, 2, 4, 5, or postgrad2
annual_salaryYesAnnual gross salary in GBP

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

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds no further behavioural context (no assumptions about tax year, thresholds, or whether the result is a pure estimate), and its return-value listing is redundant given an output schema exists.

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?

Two short sentences, front-loaded with the core purpose. The second sentence's inline return-shape enumeration is somewhat redundant against the existing output schema, but it is compact and harmless.

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?

For a simple two-parameter, one-required, read-only calculator with an output schema, the description covers what is needed to invoke it correctly. It could be stronger by noting which UK plan applies in which nation/period, but nothing essential is missing.

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 description coverage is 100%, so both parameters are already documented in the schema including the enum values for plan and the GBP unit for salary. The description merely echoes 'plan type and salary' without adding format, default, or edge-case meaning, which is the expected baseline when the schema does the work.

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?

The description states a specific verb and resource ('Calculate UK student loan repayments') and names the two drivers (plan type, salary), which separates it from the many other tax/finance siblings. It does not explicitly contrast itself with the near-neighbour calculate_student_loan_repayment or calculate_us_student_loan, so it stops short of full sibling differentiation.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance and no mention of the closely-named sibling tools that an agent could easily confuse this with. The 'See list_bundles' line is a discovery pointer, not a usage rule, so the agent must infer applicability from the tool name alone.

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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