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Calculate Belgian Pension

calculate_belgian_pension
Read-onlyIdempotent

Estimate Belgian retirement pension based on career years and average salary. Use for retirement planning in Belgium. Inputs: years of contribution, average salary, status (employee/self-employed). Returns monthly pension estimate. See list_bundles for related 'finance-belgique' calculators.

Input Schema

NameRequiredDescriptionDefault
career_yearsYesNumber of career years
average_salaryYesAverage annual salary in euros
household_typeNoPension type: single rate (60%) or household rate (75%)single

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

A3.5/5.0
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 covered. The description adds that a monthly pension estimate is returned, which is modest added context, but nothing about assumptions or edge cases (e.g. career_years capped at 45).

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?

Front-loads the core purpose, then inputs, return, and a cross-reference. Mostly efficient, though the 'See list_bundles' pointer and the 'Inputs:' enumeration add some noise given the schema already lists them.

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

Completeness3/5

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

An output schema exists so return values need not be explained, and the description covers purpose and context adequately. However the incorrect parameter characterization leaves an agent that trusts the description to supply the wrong enum values.

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 baseline is 3, but the description actively misleads: it describes an input as 'status (employee/self-employed)' while the actual schema parameter is household_type with enum single/household (60%/75% rates). This contradicts rather than clarifies the schema.

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?

States a specific verb (Estimate) and a precisely scoped resource (Belgian retirement pension), which distinguishes it from the many generic siblings like calculate_retirement_pension or calculate_swiss_lpp. An agent can identify it without opening the schema.

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 retirement planning in Belgium' implies a context but names no alternatives or exclusions, even though siblings like calculate_retirement_pension (generic) and calculate_retirement_date exist. The agent must infer when this Belgian-specific tool is preferred.

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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