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 behavioral context beyond annotations: it specifies the return format (Katzilla envelope with data, quality, citation), explains quality scoring (freshness/uptime/confidence), and details citation components (source URL, license, SHA-256 hash). This provides important implementation details not covered by 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 three sentences: first establishes scope and source, second specifies update frequency, third details return format and components. Every sentence adds essential information with zero wasted words, making it easy to parse and understand quickly.

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 presence of comprehensive annotations, 100% schema coverage, and an output schema (implied by the detailed return format description), the description provides complete context. It covers data scope, source, update frequency, return format structure, and quality metrics—everything needed for effective tool use without redundancy.

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, the input schema already fully documents both parameters (query and limit). The description does not add any parameter-specific semantics beyond what's in the schema, such as query syntax examples or limit usage guidance. The baseline score of 3 is appropriate when the schema carries the full parameter documentation burden.

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: retrieving UK health statistics from NHS England across multiple domains (hospital performance, waiting times, etc.). It specifies the data source (NHS England under Open Government Licence) and update frequency (daily), and distinguishes itself from sibling tools by focusing on UK health data rather than other categories like agriculture, crime, or economics.

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 implicitly suggests usage for UK health data queries, but does not explicitly state when to use this tool versus alternatives like health__cdc-data or health__nhs-scotland. It provides context about the data source and update frequency, which helps inform usage decisions, but lacks explicit comparison or exclusion criteria.

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