Global Economic Data

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

With no annotations, the description carries the full burden. It identifies the data source and supported indicators, but does not disclose update frequency, data freshness, error handling for invalid codes, or any access limitations. The schema provides defaults and example values, but behavioral traits beyond source are missing.

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?

Two efficient sentences front-load the purpose and content. Every sentence adds value without extraneous detail, achieving high density of useful information for an agent.

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?

Without output schema or annotations, the description should clarify the return format or data structure. It only states 'Get global GDP...' without describing the response shape. Combined with missing usage differentiation, it leaves the agent needing additional inference.

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 the schema already documents each parameter's meaning, defaults, and examples. The description adds minimal value beyond listing supported indicators in prose, which is redundant with the schema. Baseline 3 is appropriate.

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 retrieves global GDP and macroeconomic indicators from the IMF World Economic Outlook, listing specific indicators (GDP growth, inflation, government debt, current account, GDP per capita) and major economies. This provides a specific verb and resource, distinguishing it from siblings by 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?

No guidance is given on when to use this tool versus its siblings (get_oecd_indicators, get_world_bank_data). The description does not mention circumstances where this tool is preferred or where others might be better, leaving the agent without decision support.

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, and the description does not disclose behavioral traits such as read-only nature, authentication requirements, rate limits, data freshness, or output format. For a data retrieval tool, more transparency is 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 a single, clear sentence that front-loads the purpose. Every word is functional, with no extraneous information, making it highly concise.

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 parameters and no output schema, the description is adequate but does not explain the return format or any edge cases. It covers the basics but lacks completeness for an agent to fully anticipate the tool's behavior.

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%, with both parameters described in detail in the schema. The description adds context by listing topics and default countries, but largely repeats schema information, offering marginal added value.

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 retrieves OECD country comparison data for G7 and major economies, listing three specific topics. It differentiates from sibling tools by specifying the data source (OECD) and the specific indicators, but does not explicitly contrast with alternatives.

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 does not provide any guidance on when to use this tool versus its siblings (get_global_gdp, get_world_bank_data). There is no mention of prerequisites, exclusions, or alternative contexts.

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?

With no annotations provided, the description carries full burden but only lists indicators. It does not disclose behavior such as data freshness, authentication needs, rate limits, or what happens if no data is available.

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, well-structured sentence that is concise and informative. No unnecessary words.

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 simplicity of the tool (3 optional parameters, no output schema), the description covers the core functionality. However, missing usage guidelines and behavioral context slightly reduce completeness.

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% and each parameter has a detailed description including defaults and examples. The tool description adds context about covered indicators but does not significantly enhance understanding 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 retrieves World Bank development indicators for major countries and lists specific indicators (GDP, population, etc.). It distinguishes from siblings like get_global_gdp and get_oecd_indicators by specifying the data source and coverage.

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 use for World Bank data but lacks explicit guidance on when to use this tool versus alternatives (e.g., for OECD data use get_oecd_indicators). No when-not or context for selection.

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