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Glama

Global Economic Data

get_world_bank_data

Get development indicators from the World Bank for major countries. Covers GDP, population, inflation, unemployment, GDP per capita, and Gini index.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mrvNoMost recent values count (default: 1)
countriesNoSemicolon-separated ISO-2 country codes (default: US;CN;DE;GB;JP;FR;IN;BR;CA;AU)US;CN;DE;GB;JP;FR;IN;BR;CA;AU
indicatorNoWorld Bank indicator: NY.GDP.MKTP.CD (GDP $), SP.POP.TOTL (population), FP.CPI.TOTL.ZG (inflation), SL.UEM.TOTL.ZS (unemployment), NY.GDP.PCAP.CD (GDP per capita), SI.POV.GINI (Gini)NY.GDP.MKTP.CD

Schema Changelog

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

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

No annotations provided, so description bears full burden. It indicates a read operation ('Get'), but does not disclose side effects, authentication, rate limits, or return format. The description is minimal but not misleading.

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?

Single sentence, efficient, front-loaded with main action. No wasted words or redundancy.

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?

No output schema, and description does not explain return format. Sibling tools exist but no comparison. Parameters are well-documented, but overall completeness for a data-fetching tool is lacking in explaining what the response looks like.

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%, with descriptions for all parameters. The tool description lists indicator names, slightly adding value over schema's code-centric descriptions. However, no new meaning beyond what schema provides for other parameters (mrv, countries). Baseline 3.

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 clearly states it gets development indicators from the World Bank, listing specific indicators and scope (major countries). The name and description match, and it distinguishes from siblings (get_global_gdp, get_oecd_indicators) by covering multiple indicators and data source.

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 implies usage for general development indicators, but does not explicitly state when to use versus alternatives (siblings). However, the listing of indicators and source provides clear context. Exclusions or when-not-to-use are missing.

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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TDQS

A3.7/5.0
Disambiguation4/5

The tools are mostly distinct by data source (IMF, OECD, World Bank), but there is overlap in indicators like GDP, which could cause confusion. Descriptions help clarify the focus of each tool.

Naming Consistency5/5

All tool names follow a consistent 'get_SOURCE_WHAT' pattern using snake_case, making them predictable and easy to understand.

Tool Count4/5

Three tools for global economic data from major institutions is reasonable, though slightly minimal given the broad domain.

Completeness3/5

The tools cover key data sources but lack finer control such as country selection, date ranges, or additional economic indicators, leaving notable gaps.

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