Katzilla MCP

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds valuable context beyond annotations: it specifies the data source authority, update frequency ('updates daily'), and details about the return format ('Katzilla envelope { data, quality, citation }') including quality metrics and citation components. This provides useful behavioral context without contradicting 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 states purpose and scope, the second details return format and source information. Every element adds value without redundancy, and key information is front-loaded appropriately.

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 has comprehensive annotations (read-only, non-destructive, idempotent, open-world), 100% schema coverage, and an output schema (implied by the description of return format), the description provides complete context. It covers purpose, data source, update frequency, and return structure, making it fully adequate for agent understanding.

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. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain seriesId patterns or year constraints further). With complete schema coverage, the baseline score of 3 is appropriate as the description doesn't enhance parameter understanding.

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 explicitly states the action ('Fetch time-series data'), the source ('Bureau of Labor Statistics'), and the scope ('Covers CPI, unemployment, employment, and other labor statistics'). It clearly distinguishes this as a BLS-specific tool among many economic data siblings like FRED or World Bank tools, providing specific verb+resource+scope differentiation.

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 for BLS labor statistics data but doesn't explicitly state when to use this versus alternatives like 'economic__fred-series' or 'economic__bea-gdp'. It mentions the data source and coverage but lacks explicit guidance on tool selection criteria or exclusion scenarios.

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