Frankfurter MCP

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

The description adds valuable behavioral context beyond annotations: it explains the fallback mechanism ('If there is no exchange rate available for the specific date, the rate for the closest available date before the specified date will be used'). Annotations provide readOnlyHint=true and openWorldHint=true, which the description doesn't contradict. The description enhances understanding of the tool's behavior with historical data.

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 extremely concise and front-loaded: the first sentence states the core purpose, and the second sentence adds crucial behavioral detail about fallback logic. Every sentence earns its place with no wasted words. The structure is clear and efficient for an AI agent to parse.

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 moderate complexity (currency conversion with date specificity), the description is reasonably complete. It covers the core purpose and important behavioral nuance (fallback logic). With annotations covering safety (readOnly) and data scope (openWorld), and no output schema, the description provides adequate context for an agent to understand when and how to use this tool, though it could benefit from more explicit sibling differentiation.

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 all parameters well-documented in the schema (amount, from_currency, to_currency, specific_date). The description doesn't add significant parameter semantics beyond what the schema already provides. It mentions 'specific date' but doesn't elaborate on format or constraints beyond the schema's YYYY-MM-DD format. 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: 'Convert an amount from one currency to another using the exchange rates for a specific date.' It specifies the verb (convert), resource (currency amount), and key constraint (specific date). However, it doesn't explicitly distinguish this from sibling tools like 'convert_currency_latest' beyond the date specificity implied in the name.

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 when to use this tool (when you need conversion for a specific historical date) through its focus on date-specific rates. However, it doesn't explicitly state when to choose this over alternatives like 'convert_currency_latest' or when not to use it (e.g., for real-time conversions). The fallback behavior for missing dates provides some context but not explicit comparative guidance.

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