Global Economic Data

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

No annotations are provided, so the description must cover behavioral traits. It indicates a read-like operation (getting data) but does not disclose aspects like rate limits, data freshness, or whether it is truly read-only. The description is minimal beyond listing indicators.

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

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

The description is concise at two sentences, with the first sentence front-loading the purpose and the second listing supported indicators. It is clear and efficient, though a slight improvement could include a brief usage note.

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

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

The description covers what the tool does and the main data types, but given the lack of output schema, it omits return format or structure. For 3 parameters and no annotations, it is adequate but not fully complete – the agent may need more info on what the response looks like.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds some context by listing the types of indicators (GDP growth, inflation, etc.), but the schema already provides detailed descriptions including default values and indicator codes. The description does not significantly add meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool gets global GDP and macroeconomic indicators from the IMF World Economic Outlook, specifying the data types (GDP growth, inflation, etc.). It distinguishes from siblings by naming the source (IMF WEO), which differentiates it from get_oecd_indicators and get_world_bank_data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for IMF data but does not explicitly state when to use this tool versus the siblings. It lists supported indicators and major economies, but lacks guidance on exclusions or context for selecting this over alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries full burden. It does not disclose any behavioral traits such as whether the operation is read-only, requires authentication, or has side effects. Given the nature of the tool, a read-only hint would be expected.

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

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

The description is extremely concise: two sentences front-load the main purpose and list the topics. Every word is relevant, with no redundancy or unnecessary detail.

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

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

Given the simple tool structure (2 parameters, no output schema, no annotations), the description covers the basic purpose and topics. However, it lacks usage guidance and behavioral transparency, leaving some gaps for complete agent decision-making.

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

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

Although the schema already describes both parameters with 100% coverage, the description adds context by specifying that 'interest_rates' is long-term, 'trade_balance' is current account, and that the data is for G7 and major economies, which adds meaning beyond the schema's enumeration.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'OECD country comparison data for G7 and major economies', listing three specific topics. This distinguishes it from sibling tools like 'get_global_gdp' and 'get_world_bank_data' which focus on different data sources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for OECD country comparison data for the listed topics, but it does not explicitly state when to use this tool versus alternatives, nor does it provide any exclusions or conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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.

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.

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.

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.

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.

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.