Katzilla MCP

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

The description adds valuable behavioral context beyond annotations: it discloses the return format (Katzilla envelope with data, quality, citation), explains what quality scores measure (freshness/uptime/confidence), and describes citation contents (source URL, license, SHA-256 hash). While annotations cover read-only/non-destructive/idempotent/open-world aspects, the description provides important implementation details about output structure and auditability.

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, scope, and parameters; the second explains the return format and its components. Every element serves a clear purpose with no wasted words, and key information is 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 comprehensive annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), 100% schema coverage, and the presence of an output schema (implied by the detailed return format description), the description provides complete context. It covers purpose, usage context, behavioral traits, and output structure without needing to duplicate structured field information.

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?

With 100% schema description coverage and clear enum values for 3 of 4 parameters, the schema already documents parameter semantics thoroughly. The description mentions 'broken down by age and sex' and 'seasonally adjusted' which aligns with parameters but doesn't add significant meaning beyond what the schema provides. The baseline of 3 is appropriate when the schema does most of the work.

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 retrieves 'Monthly and annual unemployment rates from Eurostat for EU/EEA countries' with specific breakdowns by 'age and sex' and seasonal adjustment status. It distinguishes itself from sibling tools like economic__eurostat-gdp or economic__eurostat-inflation by focusing specifically on unemployment data.

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 about when to use this tool: for European labour market analysis with Eurostat unemployment data. It mentions the data source and update frequency, but doesn't explicitly state when not to use it or name specific alternatives among the many economic sibling tools.

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