countries

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

With no annotations provided, the description carries the full burden. It discloses the return format ('name, capital, and region'), which is helpful, but lacks details on error handling, rate limits, or authentication needs. No contradiction with annotations exists.

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 with two sentences: one stating the purpose and one specifying the return format. It is front-loaded and wastes no words, making it highly efficient.

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 (1 parameter, no output schema, no annotations), the description is mostly complete. It covers purpose and return values, but could improve by addressing behavioral aspects like error cases or usage context.

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 the 'currency' parameter. The description does not add meaning beyond what the schema provides, such as examples or edge cases, meeting the baseline for high coverage.

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 ('Find') and resource ('all countries that use a given currency'), and distinguishes it from siblings by focusing on currency-based lookup rather than language, region, code, or general search.

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 when currency-based country lookup is needed, but does not explicitly state when to use this tool versus alternatives like 'countries_by_language' or 'search_countries'. No exclusions or prerequisites are mentioned.

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 the full burden of behavioral disclosure. It indicates the tool returns specific fields, implying a read-only operation, but does not mention potential limitations like partial matches, case sensitivity, or error handling. It adds some context (return fields) but lacks details on performance, rate limits, or data freshness.

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, efficient sentence that front-loads the core purpose and follows with return details. Every word earns its place, with no redundancy or unnecessary elaboration, making it easy for an agent to parse quickly.

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 (one parameter, no output schema, no annotations), the description is adequate but has gaps. It explains what the tool does and what it returns, but lacks usage guidelines and behavioral details like error cases or data scope. It meets minimum viability but could be more complete for optimal agent use.

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 input schema has 100% description coverage, so the parameter 'language' is well-documented in the schema. The description adds no additional parameter details beyond implying the tool uses this input, but with only one parameter and high schema coverage, the baseline is 3. The description's clarity on output compensates slightly, raising it to 4.

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 ('Find all countries where a given language is spoken') and the resource ('countries'), distinguishing it from siblings like countries_by_currency or countries_by_region. It also specifies the exact return fields (name, capital, region, population), making the purpose unambiguous.

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 no guidance on when to use this tool versus alternatives such as search_countries or get_country_by_code. It mentions the parameter 'language' but does not specify use cases, exclusions, or comparisons to sibling tools, leaving the agent to infer usage from the tool name alone.

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 for behavioral disclosure. It states it's a list operation but doesn't mention whether it's read-only, if there are rate limits, authentication needs, pagination behavior, or error handling. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves beyond basic functionality.

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, well-structured sentence that efficiently communicates the tool's purpose, scope, and output. Every word earns its place with no redundancy or unnecessary information, making it appropriately sized and front-loaded.

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 single parameter with full schema coverage and no output schema, the description adequately covers the basic functionality. However, it lacks details about behavioral aspects (rate limits, errors, etc.) and doesn't explain the return format beyond listing fields, leaving some gaps in completeness for practical use.

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 the region parameter fully documented in the schema (including allowed values). The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline score of 3 where the schema does the heavy lifting.

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 ('List all countries'), target resource ('in a geographic region'), and output fields ('with name, capital, population, and flag'). It distinguishes from siblings like 'countries_by_currency' or 'search_countries' by specifying region-based filtering rather than currency, language, code, or general search.

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 retrieving countries by region, but provides no explicit guidance on when to use this tool versus alternatives like 'countries_by_currency' or 'search_countries'. It mentions the region parameter but doesn't clarify scenarios where region-based listing is preferred over other filtering methods.

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 describes the lookup behavior but lacks details on error handling (e.g., invalid codes), rate limits, authentication needs, or what 'full country information' includes. This is a significant gap for a tool with no annotation coverage.

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, efficient sentence with zero waste. It is front-loaded with the core purpose and includes necessary examples, making it appropriately sized and well-structured.

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 (1 parameter, no nested objects) and high schema coverage, the description is adequate but incomplete. It lacks output details (no output schema) and behavioral context, which is needed for full understanding, especially with no annotations.

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 the parameter. The description adds minimal value by reiterating the code format (ISO 3166-1 alpha-2/alpha-3) and providing examples ('US', 'USA'), but no additional semantics 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 tool's purpose with a specific verb ('Get') and resource ('full country information'), and it distinguishes from siblings by specifying the lookup method (by ISO code) rather than by currency, language, region, or search.

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 context by specifying the input format (ISO codes), but it does not explicitly state when to use this tool versus alternatives like 'search_countries' or other sibling tools. No exclusions or prerequisites are mentioned.

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 the full burden of behavioral disclosure. It adds value by specifying the return fields (common name, official name, capital, etc.) and flag emoji, which helps understand output format. However, it doesn't mention behavioral traits like rate limits, error handling, or whether the search is case-sensitive, leaving gaps in transparency.

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 with two sentences: one stating the purpose and parameter, and another detailing the return values. It's front-loaded with the core functionality, and every sentence adds value without waste. However, it could be slightly more structured by separating usage guidance from output details.

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 (1 parameter, no annotations, no output schema), the description is somewhat complete but has gaps. It covers the purpose and output fields, which is helpful, but lacks details on behavioral aspects like performance or limitations. Without annotations or output schema, more context on usage and results would improve 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%, so the schema already documents the 'query' parameter with its type and description. The description adds minimal semantics beyond the schema by implying the search is by name, but it doesn't provide additional details like search algorithm or match specificity beyond what's in the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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: 'Search for countries by name' specifies the verb (search) and resource (countries). It distinguishes from siblings by focusing on name search rather than currency, language, region, or code-based lookup. However, it doesn't explicitly mention how it differs from siblings beyond the search parameter.

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 context through 'Search for countries by name,' suggesting this tool is for name-based queries. However, it doesn't provide explicit guidance on when to use this vs. alternatives like 'countries_by_currency' or 'get_country_by_code,' nor does it mention any exclusions or prerequisites for usage.

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