Katzilla MCP

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

Annotations already indicate read-only, non-destructive, idempotent, and open-world behavior. The description adds valuable context beyond this: it specifies the source (Datamuse), licensing (Free / Attribution), update frequency (daily), and details about the return format (Katzilla envelope with quality scores and citation). This enhances the agent's understanding of reliability and data provenance.

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 the purpose and search types, and the second covers source, licensing, updates, and return format. Every sentence adds essential information without redundancy, making it front-loaded and concise.

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 moderate complexity, rich annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), 100% schema coverage, and the presence of an output schema, the description is complete. It covers purpose, usage context, behavioral traits, source details, and return format, leaving no significant gaps for the agent to operate effectively.

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 the parameters (query, type, limit). The description adds minimal parameter semantics by mentioning the search types (meaning, sound, spelling, rhyme) but does not provide additional syntax or format details beyond what the schema already specifies. This meets the baseline for high schema coverage.

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: 'Find words using the Datamuse API — search by meaning, sound, spelling, or rhyme.' It specifies the verb ('Find words'), resource ('Datamuse API'), and scope (four search types), distinguishing it from sibling tools which cover unrelated domains 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 provides clear context for usage by listing the four search types (ml, sl, sp, rel_rhy) and mentioning the source (Datamuse) and update frequency (daily). However, it does not explicitly state when to use this tool versus alternatives or include any exclusions, such as when other word-related tools might be more appropriate.

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