exchange

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 mentions 'current exchange rate' but doesn't specify source, update frequency, or accuracy. It lacks details on error handling, rate limits, authentication needs, or what happens with invalid inputs. For a financial tool with zero 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 a single, efficient sentence that directly states the tool's function. It's front-loaded with the core purpose and contains no unnecessary information. Every word earns its place, making it highly concise 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 complexity (financial conversion with real-time data implications), no annotations, and no output schema, the description is incomplete. It doesn't explain return values, error cases, or behavioral nuances like rate freshness. For a tool with these characteristics, more context is needed to be fully helpful to an AI agent.

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 description implies parameters (from, to, amount) but doesn't add meaning beyond what the input schema provides. With 100% schema description coverage, the schema already documents all three parameters clearly. The description doesn't provide additional context like currency code formats or amount constraints, so it meets the baseline for high schema 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: converting an amount between currencies at current exchange rates. It specifies the verb ('convert') and resources ('amount from one currency to another'), but doesn't explicitly distinguish it from sibling tools like get_rate or get_historical_rate, which are related but serve different purposes.

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. It doesn't mention sibling tools like get_currencies, get_historical_rate, or get_rate, nor does it specify scenarios where this conversion tool is preferred over those alternatives. There's no context about prerequisites or limitations.

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 describes the action as a list operation, implying read-only behavior, and specifies the data source (Frankfurter API) and output detail ('full names'). However, it does not mention potential limitations like rate limits, error handling, or response format beyond the names.

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 action ('List all currencies') and includes essential details (API source and output format) without any wasted words. Every element serves a clear purpose.

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 (0 parameters, no output schema, no annotations), the description is complete enough for a simple list operation. It specifies the API source and output detail, though it could benefit from mentioning the response structure or any constraints to achieve full 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately adds value by explaining the tool's purpose and output without redundant parameter details, earning a baseline score of 4 for zero-parameter tools.

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 currencies') and resource ('supported by the Frankfurter API'), distinguishing it from sibling tools like convert, get_historical_rate, and get_rate. It explicitly mentions 'with their full names' to specify the output scope.

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 'supported by the Frankfurter API' and the output format, but does not explicitly state when to use this tool versus alternatives like get_rate or get_historical_rate. It provides clear context but lacks explicit exclusions or comparisons.

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 states the basic operation but lacks behavioral details like rate limits, authentication needs, error conditions (e.g., invalid dates or currencies), data source, or return format. The description doesn't contradict annotations (none exist).

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 with no wasted words. Every element ('Get', 'exchange rate', 'two currencies', 'specific historical date', 'YYYY-MM-DD') contributes directly to understanding the tool.

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 for a tool with 3 parameters. It covers the basic operation but lacks critical context like return value structure, error handling, data freshness, or limitations (e.g., date range constraints beyond the schema's 'earliest available' note).

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%, providing clear parameter documentation. The description adds minimal value beyond the schema by reinforcing the date format (YYYY-MM-DD) and historical context, but doesn't explain parameter interactions or provide additional semantics like currency code examples beyond what's in 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 specific action ('Get the exchange rate') and resource ('between two currencies on a specific historical date'), using a precise verb. It distinguishes from sibling tools like 'get_rate' (likely current rate) and 'convert' (likely conversion operation) by specifying the historical aspect.

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 ('on a specific historical date') but doesn't explicitly state when to use this tool versus alternatives like 'get_rate' (presumably for current rates) or 'convert' (presumably for actual conversions). 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 states the tool retrieves current exchange rates but lacks details on data sources, accuracy, rate limits, error handling, or response format. This is a significant gap for a tool that likely relies on external APIs.

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 with an illustrative example. There's zero waste, and it's appropriately sized for a simple tool with two parameters.

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 complexity (simple but with potential external dependencies), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like rate limits, data freshness, or error cases, which are critical for an exchange rate tool. More context is needed for reliable 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 clear parameter descriptions in the schema. The description adds minimal value beyond the schema by providing an example (e.g., USD to EUR) but doesn't explain parameter constraints or usage beyond what's already documented. Baseline 3 is appropriate given high schema 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 ('Get') and resource ('exchange rate between two currencies'), including an example. It distinguishes from sibling tools by focusing on current rates rather than conversion, historical data, or currency lists, though it doesn't explicitly name 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?

Usage is implied through the description's focus on 'current exchange rate,' suggesting this tool is for real-time rates rather than historical data (get_historical_rate) or currency conversion (convert). However, there's no explicit guidance on when to use this versus siblings or any prerequisites.

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