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, covering safety and idempotency. The description adds valuable context beyond annotations: it specifies the data source ('National Park Service (Public Domain), updates annual'), describes the return format ('Katzilla envelope { data, quality, citation }'), and explains quality metrics ('freshness/uptime/confidence') and citation details ('source URL, license, SHA-256 data hash'). No contradictions with annotations exist.

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 the core purpose in the first sentence, followed by additional context in a structured manner. Every sentence adds value: the first defines the action and scope, the second specifies the source and update frequency, and the third details the return format and its components. No wasted words or redundancy.

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 (search operation with quality metrics), rich annotations (covering safety and idempotency), and the presence of an output schema (implied by 'Returns the Katzilla envelope'), the description is complete. It explains the data source, update frequency, return structure, and audit features, compensating well for any gaps not covered by structured fields.

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 both parameters ('query' and 'limit') well-documented in the input schema. The description does not add any parameter-specific semantics beyond what the schema provides (e.g., it doesn't clarify query syntax or limit implications). Baseline score of 3 is appropriate since the schema handles parameter documentation adequately.

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 ('search', 'find') and resources ('National Park Service lesson plan database', 'educational resources about national parks, history, science, and the environment'). It distinguishes itself from sibling tools like 'education__college_scorecard' or 'education__uk_education' by focusing on NPS lesson plans rather than other educational datasets.

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 stating it searches for 'educational resources about national parks, history, science, and the environment', but it does not explicitly state when to use this tool versus alternatives (e.g., other education tools like 'education__college_scorecard' or general search tools). No exclusions or prerequisites are mentioned.

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