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Glama

AgentWorld

get_city_stats

[FREE] Get stats for AgentWorld cities: agent count, avg wealth, GDP, pay multiplier. Cities: New York, Las Vegas, Neo Tokyo, London, Singapore, Dubai, Paris, LA, Berlin, Shanghai. Paris 1.4x | Singapore 1.35x | Dubai 1.25x | London 1.15x | Others 1.0x. Leave city empty to get all 10 cities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden, and it does disclose important behavior: the tool is marked FREE, returns specific stats, applies fixed pay multipliers per city, and treats an empty city as 'all cities'. This goes beyond a bare 'get stats' statement, though it stops short of describing error behavior or explicit read-only guarantees.

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

Conciseness5/5

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

The description is compact and front-loaded: the core purpose and metrics appear first, followed by the city list, multiplier rules, and the empty-input behavior. Every line adds useful information and none is redundant or filler.

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

Completeness5/5

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

For a one-optional-parameter read-only stats tool with an output schema, the description provides everything needed: what data is returned, which inputs are valid, and the special behavior for empty input. No critical calling information is missing.

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

Parameters5/5

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

The schema only defines 'city' as a string with a default of '', but the description compensates fully by enumerating all 10 accepted city names and explaining that an empty value returns all cities. It even clarifies the multiplier effect per city, which is essential semantic meaning absent from 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?

The description uses a specific verb-resource pair ('Get stats for AgentWorld cities') and enumerates the exact metrics returned: agent count, avg wealth, GDP, pay multiplier. It also lists all valid city names, making the tool's scope unmistakable and clearly distinguished from broader economy or leaderboard siblings.

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?

The description gives clear usage context: provide a city from the list, or leave city empty to get all 10 cities. It does not explicitly name alternative tools or state when not to use this tool, but the input behavior is explicit enough for a simple optional-parameter getter.

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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