Katzilla MCP

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

The description adds valuable behavioral context beyond the annotations: it discloses the data source (Frankfurter API), licensing (MIT License), update frequency (real-time), and return format (Katzilla envelope with quality scores and citation details). The annotations already indicate it's read-only, non-destructive, idempotent, and open-world, but the description enriches this with practical implementation details like no API key requirement and audit features, without contradicting the 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 efficiently structured in two sentences: the first covers purpose, source, and key features; the second details the return format and its components. Every sentence adds essential information without redundancy, making it front-loaded and appropriately sized for the tool's complexity.

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, rich annotations (read-only, idempotent, etc.), 100% schema coverage, and presence of an output schema, the description is complete. It covers purpose, source, licensing, update behavior, and return format, compensating well for any gaps and ensuring the agent has sufficient context without needing to rely solely on structured fields.

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 baseline is 3. The description does not add specific parameter semantics beyond what the schema provides (e.g., it doesn't explain format details for 'date' or examples for 'symbols' beyond the schema's descriptions). However, it implicitly contextualizes parameters by mentioning 'current or historical' data, which aligns with the 'date' parameter, but this is minimal added value.

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 current or historical currency exchange rates'), resource ('from the Frankfurter API'), and scope ('Supports all major currencies'). It distinguishes itself from sibling tools by focusing exclusively on exchange rates, unlike other economic tools like 'economic__bea-gdp' or 'economic__bls-series' which handle different economic indicators.

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 usage: it specifies the data source (Frankfurter API), indicates it's for currency exchange rates, and mentions it supports both current and historical data. However, it does not explicitly state when to use this tool versus alternatives (e.g., other exchange rate tools like 'economic__ecb-rates' or 'international__open-exchange'), nor does it provide exclusions or prerequisites beyond the implied currency code usage.

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