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

With no annotations, the description carries the transparency burden. It discloses the important constraint 'One side must be KZT' and the rate source, but does not mention behavior on invalid inputs, output format, or the role of the date parameter. It is adequate but not rich.

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?

One sentence of ten words, front-loaded with purpose and constraint. No unnecessary information; every part earns its place.

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 4-parameter schema with full coverage, the description provides the essential purpose and key constraint. It does not explain the return value, but for a straightforward conversion tool this is acceptable. It is reasonably complete for its complexity.

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%, so parameters are documented. The description adds semantic value by stating the critical business rule that one side must be KZT, which is not evident from the schema alone.

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 converts between currencies using NBK rates, with a specific verb and resource. It also highlights the key constraint that one side must be KZT, which distinguishes it from sibling rate-query tools.

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 conversion, but does not explicitly contrast with siblings like get_currency_rate or provide when-not-to-use guidance. The verb 'convert' suggests usage, but it is not explicit.

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 present, the description bears full responsibility for behavioral disclosure. It only states the purpose and source; it does not mention response structure, base currency, rate type (buy/sell), or any caching/authorization behavior. The agent is left to guess the output format.

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, front-loaded sentence that conveys exactly what the tool does and from where. No filler words, and it is appropriately sized for the tool's simplicity.

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 zero-parameter, no-output-schema tool, the description is reasonably complete: it names the specific source and the scope ('all current'). The main gap is the lack of output structure detail, but given the low complexity, 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 tool has zero parameters, so the schema already covers everything trivially. The baseline for zero-parameter tools is 4, and the description adds no parameter-specific meaning because none are needed.

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 function with a specific verb 'Get', a specific resource 'all current currency exchange rates', and a source 'National Bank of Kazakhstan'. It naturally distinguishes itself from siblings like get_currency_rate (single rate) and get_historical_rates (time-series).

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 phrase 'all current' implies the tool should be used when a complete snapshot of today's rates is needed, but the description does not explicitly state when to prefer it over siblings or provide exclusions. Context from sibling names helps, but the description itself lacks direct usage guidance.

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 data source but does not mention what the tool returns (e.g., numeric value), how it handles invalid currencies, whether the date defaults to today, or any rate limits. This lack of detail leaves the agent uncertain about expected behavior.

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, concise sentence with no filler or redundancy. It is front-loaded with the primary action and resource, making it easily scannable.

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 tool is simple with only two parameters and no output schema, so the description is mostly adequate. However, the lack of guidance on when to use this tool versus its siblings, and the absence of information about return format or error behavior, leaves some gaps for an agent trying to select and invoke it correctly.

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 provides complete descriptions for both parameters (currency_code and date), achieving 100% schema description coverage. The description does not add any parameter semantics beyond the schema, so the baseline of 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 action ('Get') and the resource ('exchange rate for a specific currency from the National Bank of Kazakhstan'). It distinguishes from sibling tools like get_all_rates by emphasizing 'specific currency', 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?

No guidance is provided on when to use this tool versus alternatives like get_all_rates, get_historical_rates, or convert_currency. There is no mention of prerequisites, such as needing a rate for a particular date or when to prefer this over get_rate_dynamics.

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 must carry the full burden of behavioral disclosure. While it states the source and action, it does not explain important behaviors such as date format handling (beyond schema), behavior on non-business days, the structure of the response, or any potential limitations. This is minimal disclosure that adds little beyond the basic function.

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 immediately conveys the tool's purpose. Every word serves a function, and there is no redundant information or filler.

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 provides sufficient context to understand its purpose and when to use it. It accurately conveys the input requirement and the resource returned, though it omits specifics about the return format, which is a minor gap given the simple nature.

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 covers 100% of the parameter (date) with a clear description of the expected format (DD.MM.YYYY). The tool description adds no additional semantic detail beyond the schema, so the baseline 3 is appropriate—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 function: retrieving all currency exchange rates for a specific date from the National Bank of Kazakhstan. It uses a specific verb ('Get') and identifies both the resource (currency exchange rates) and the scope (specific date, specific source), which distinguishes it from siblings like get_currency_rate (single currency) and get_rate_dynamics (time series).

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 clearly implies usage context: use this when you need all exchange rates for a particular date. It doesn't explicitly name alternatives or exclusions, but the phrase 'for a specific date' establishes a clear use case that differentiates from other tools like get_all_rates (likely current rates) or get_currency_rate.

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, the description carries the full burden. It discloses the core behavior of providing a current rate and a UP/DOWN direction indicator, but does not specify the output structure, how direction is calculated (e.g., vs previous close), or any edge cases like unavailable rates. This is acceptable but not rich.

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, front-loaded sentence that conveys the core functionality without any redundant or extraneous words. It earns a 5 for efficiency.

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 single-parameter read-only tool, the description covers the essential purpose and distinctive feature. However, the lack of any output schema and the absence of details on the return format slightly weaken completeness for an AI agent, leaving a 4 rather than a 5.

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 already fully describes currency_code with examples (USD, EUR, RUB), achieving 100% coverage. The description adds no additional parameter-specific context beyond restating that it applies to a currency, so it earns 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 'Get the current rate with change direction,' identifying the specific verb, resource, and unique scope (direction) that distinguishes this from sibling tools like get_currency_rate and get_all_rates. The addition of 'shows if rate went UP or DOWN' reinforces the distinguishing purpose.

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 when the caller needs direction information, but it does not explicitly mention alternatives or state when not to use this tool. There is no comparison to get_currency_rate for simple rate retrieval, so the usage context is only implicit, not clearly delineated.

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