worlduank

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates this is a read operation ('Get') and specifies the input format, but doesn't mention potential limitations like error handling, data freshness, or rate limits. The description adds useful context about what data is returned, compensating partially for the lack of annotations.

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 perfectly concise with two sentences: the first states the purpose and data returned, the second specifies the input format with examples. Every word earns its place with zero redundancy, and the information is front-loaded appropriately.

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?

For a simple read tool with one parameter and no output schema, the description is reasonably complete. It covers the purpose, data returned, and input requirements. The main gap is the lack of output format details, but given the tool's simplicity and the clear data fields listed, this is a minor omission.

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?

The schema description coverage is 100%, so the schema already documents the single parameter thoroughly. The description adds minimal value beyond the schema by repeating the ISO code format examples, but doesn't provide additional semantic context about parameter behavior or constraints.

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's purpose with a specific verb ('Get') and resource ('basic information about a country'), listing key data fields (full name, region, income level, capital city, coordinates). It distinguishes from siblings by focusing on general country info rather than specific metrics like GDP or population.

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 provides clear context for when to use this tool (to retrieve basic country information) and specifies the required input format (ISO 3166-1 codes). However, it doesn't explicitly state when not to use it or name alternatives among sibling tools, though the distinction is implied by the different data focus.

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 the full burden of behavioral disclosure. While it states what the tool does, it doesn't describe important behavioral aspects like whether this is a read-only operation, what format the data returns in, whether there are rate limits, or what happens with invalid country codes. For a tool with no annotation coverage, this is a significant gap.

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 perfectly concise with two sentences that each earn their place: the first states the core purpose, the second provides crucial sibling differentiation. There's zero wasted language and it's effectively front-loaded with the most important information.

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?

For a single-parameter read tool with 100% schema coverage, the description provides adequate context about purpose and sibling relationships. However, with no output schema and no annotations, it doesn't describe what format the GDP data returns in (time series? single value? error handling?), which leaves gaps in understanding the tool's complete 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%, so the schema already fully documents the single parameter (country_code with ISO code format). The description doesn't add any parameter-specific information beyond what's in the schema, so the baseline score of 3 is appropriate when the schema does all the parameter documentation work.

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 specific action ('Get GDP'), resource ('current USD over time for a country'), and scope ('shortcut for get_indicator with NY.GDP.MKTP.CD'). It precisely distinguishes this tool from its sibling 'get_indicator' by specifying it's a specialized version for GDP 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 explicitly states when to use this tool ('shortcut for get_indicator with NY.GDP.MKTP.CD'), providing clear context and an alternative (using get_indicator directly). This gives the agent perfect guidance on when this specialized tool is appropriate versus the more general sibling.

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 the full burden. It mentions retrieving time-series values but lacks details on permissions, rate limits, data freshness, or error handling. This is a significant gap for a data-fetching tool with no structured safety hints.

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 appropriately sized and front-loaded, with a clear purpose in the first sentence and efficient examples in the second. Every sentence adds value without 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?

Given no annotations and no output schema, the description is incomplete. It covers the basic purpose and parameters but lacks details on return values, error cases, or behavioral constraints, which are needed for a tool fetching time-series data.

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 all parameters. The description adds value by providing common indicator examples (e.g., NY.GDP.MKTP.CD) and implying time-series output, but it does not explain parameter interactions or formats beyond what the schema provides.

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 specific action ('Get time-series values') for a specific resource ('World Bank indicator for a specific country'), distinguishing it from siblings like get_gdp or get_population by indicating it handles multiple indicators through codes.

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 provides clear context by listing common indicator examples (e.g., GDP, population), which helps guide usage, but it does not explicitly state when to use this tool versus alternatives like get_gdp or get_population, nor does it mention exclusions.

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. While it mentions this is a 'shortcut' for another tool, it doesn't disclose key behavioral traits like whether this is a read-only operation, what format the 'over time' data returns (e.g., time series), potential rate limits, or error conditions. The description adds minimal behavioral context beyond the basic purpose.

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 perfectly concise with two sentences: the first states the purpose, and the second provides crucial usage guidance. Every word earns its place, and it's front-loaded with the core functionality.

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 tool's low complexity (single parameter, no annotations, no output schema), the description is adequate but has gaps. It explains the purpose and sibling relationship well, but without annotations or output schema, it should ideally mention more about the return format (e.g., time series data) or behavioral constraints to be fully complete.

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 fully documents the single parameter 'country_code' with its type, requirement, and format example. The description doesn't add any parameter-specific information beyond what the schema provides, maintaining the baseline score of 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 the specific action ('Get total population over time') and resource ('for a country'), and explicitly distinguishes this tool from its sibling 'get_indicator' by calling it a 'shortcut' for that specific indicator code. This provides excellent differentiation.

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 explicitly states when to use this tool versus alternatives: it's a 'shortcut for get_indicator with SP.POP.TOTL.' This tells the agent precisely when to choose this tool (for population data) versus the more general 'get_indicator' tool or other siblings like 'get_country' or 'get_gdp'.

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