Katzilla MCP

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds valuable context beyond annotations: it specifies the data source (Analytics.usa.gov), update frequency (daily), and return format (Katzilla envelope with quality scores and citation details including SHA-256 hash). This enhances transparency 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 front-loaded with core functionality, followed by source and return details in two efficient sentences. Every sentence adds value: the first defines purpose and scope, the second specifies source, updates, and output structure, with no wasted words.

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 (data access with parameters), rich annotations (read-only, idempotent, open-world), and output schema (implied by return format description), the description is complete. It covers purpose, source, update frequency, and output structure, compensating for any gaps without needing to repeat schema details.

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%, so the schema fully documents parameters (report, limit, after). The description does not add parameter-specific semantics beyond what the schema provides, such as explaining report types or date formats. Baseline 3 is appropriate as the schema carries the 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 'access[es] federal website analytics data from the Digital Analytics Program (DAP) including visits, pageviews, and users,' specifying the verb ('access'), resource ('federal website analytics data'), and data types. It distinguishes from siblings by focusing on U.S. government analytics, unlike other tools in the list that cover agriculture, crime, or other domains.

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 accessing federal analytics data, but does not explicitly state when to use this tool versus alternatives (e.g., other government data tools like 'government__datagov' or 'government__site-scanning'). It mentions the source and update frequency, providing some context, but lacks clear exclusions or comparisons.

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