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Compare prostitution laws between countries

compare_countries
Read-onlyIdempotent

A side-by-side table of how 2 to 10 countries regulate prostitution: the legal model and the status of each chosen question (default: selling, buying, brothels, procuring, advertising), with a link to each full profile.

Input Schema

NameRequiredDescriptionDefault
topicsNoThe questions to compare (default: selling, buying, brothels, procuring, advertising). One of: selling (selling sexual services), buying (buying sexual services), brothels (brothels and managed venues), sharedPremises (sex workers sharing premises), procuring (third parties profiting (procuring / pimping)), advertising (advertising sexual services), platforms (online platforms and ad sites), street (street-based sex work and soliciting), registration (registration, licensing and health checks), tax (tax and social security), migrants (migrant sex workers).
countriesYesThe countries to compare (names or ISO codes).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so safety is covered. The description adds real behavioral value beyond that: the output is a table, the topic set is defaulted when omitted, and each row carries a link to the full profile. It does not say what happens for an unrecognized country, which is the remaining gap.

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?

A single front-loaded sentence that leads with the output shape and packs the default topic list inline with no filler. It is dense but every clause carries information; a slightly shorter default listing would make it crisper.

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?

There is no output schema, and the description compensates by describing the returned table (legal model column, per-question statuses, profile links) plus the default topic behavior. Combined with a fully documented schema and read-only annotations, only error/invalid-country handling is left unexplained.

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%, so both parameters are already fully documented in the schema, including the topic enum meanings and country name/ISO examples. The description only restates the defaults and the 2–10 bound, adding no semantics beyond the structured fields. Baseline 3 applies.

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+resource: a side-by-side comparison table of 2–10 countries' prostitution regulation, including what columns come back. It implicitly separates itself from get_country_law (single full profile) via the 'link to each full profile' phrasing, but never names the sibling explicitly.

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?

The 2-to-10 country range and the default topic set are given, which scopes usage, but there is no explicit 'use this when you need to compare rather than look up one country' guidance nor a pointer to get_country_law for the detail behind a link. Usage is inferred from the output shape.

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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