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UAE end-of-service gratuity estimate

uae_gratuity
Read-onlyIdempotent

AED estimate for covered private-sector full-time foreign workers using monthly basic salary, at least one year service, 21 days for first five years then 30; capped at 24 months basic salary. Assumes continuous service without unpaid leave; no deductions or alternative schemes assessed. Free, no authentication required. Rate limited.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endDateYes
startDateYes
basicSalaryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
currencyYes
eligibleYes
gratuityYes
yearsOfServiceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish the safe-read profile (readOnly, idempotent, non-destructive, closed-world), so the description earns credit for the extra operational context it adds: free, no authentication required, rate limited, and the key modeling assumption of continuous service without unpaid leave. It does not quantify the rate limit or describe the response shape, but the added constraints are genuinely useful.

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?

It is front-loaded with the result type and eligibility, then layers the calculation rule, cap, assumptions, and access notes. Dense but every clause carries information; the long semicolon-joined sentences are the only mild readability cost.

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?

An output schema exists, so return values need not be explained. The description supplies eligibility, the accrual formula, the 24-month cap, modeling assumptions, and access constraints. What is missing is only peripheral detail such as date-format expectations and what happens for sub-one-year service.

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 0%, so the description must carry the parameter burden. It clarifies that the salary input is monthly basic salary (not gross or allowances), which is meaningful disambiguation, and the service-period requirement implicitly maps to startDate/endDate. However, it says nothing about the expected date format or how partial-year service is handled, leaving two of three parameters only loosely covered.

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?

The description names a specific verb and resource (an AED end-of-service gratuity estimate) and pins down the population it applies to: covered private-sector full-time foreign workers. That scope makes it unmistakable against siblings like uae_vat or uae_corporate_tax, which cover entirely different obligations.

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?

It states the qualifying conditions clearly (covered private-sector, full-time, foreign, at least one year of service) and rules out related-but-unsupported cases (no deductions or alternative schemes assessed). It does not, however, name or route to any alternative tool for those excluded cases, so it stops short of explicit when-not/alternatives guidance.

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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