Katzilla MCP

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

Annotations already cover read-only, non-destructive, idempotent, and open-world hints. The description adds valuable behavioral context beyond annotations: it specifies the data source (World Bank), update frequency (monthly), license (CC BY-4.0), and return format (Katzilla envelope with quality scores and citation details including SHA-256 hash). This enriches the agent's understanding of data reliability 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 and scope, the second details source, updates, and return format. Every sentence adds critical information without redundancy, making it front-loaded and zero-waste.

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 complexity (7 parameters, read-only operation) and rich annotations/output schema, the description is complete. It covers purpose, data scope, source, update frequency, license, and return structure—compensating well for any gaps. With an output schema present, it doesn't need to explain return values in detail.

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 each parameter well-documented in the schema (e.g., country as ISO code, indicator examples). The description adds minimal parameter semantics beyond the schema, only implying indicator types (GDP, population) without new syntax or constraints. Baseline 3 is appropriate since 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 purpose with specific verbs ('Fetch development indicators') and resources ('from the World Bank API'), covering key domains like GDP, population, and health. It distinguishes itself from sibling tools (e.g., economic__bea-gdp, economic__fred-series) by specifying it's for World Bank data, not other economic sources.

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 context by listing indicator types (GDP, population, etc.) and mentioning monthly updates, but it lacks explicit guidance on when to use this tool versus alternatives like economic__bea-gdp or economic__fred-series. No when-not-to-use or prerequisite information is provided.

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