Ontology MCP

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states what the tool does (retrieves model list) but doesn't describe how it behaves: no information about response format, whether it requires authentication, rate limits, freshness of data, or error conditions. For a tool with zero annotation coverage, this is insufficient behavioral context.

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 a single, efficient sentence in Korean that directly states the tool's function. It's appropriately sized for a simple list operation with no parameters. While concise, it could be slightly more informative about the tool's role in the broader context.

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?

For a tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the return value looks like (list format, model attributes), authentication requirements, or how this information should be used with sibling tools. Given the complexity of model selection in AI systems, more context about the output would be valuable.

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?

The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema fully documents the empty input structure. No additional parameter information is needed or provided.

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 verb ('조회합니다' - retrieves/list) and resource ('사용 가능한 Gemini 모델 목록' - available Gemini model list), making the purpose understandable. It doesn't explicitly differentiate from siblings like mcp_ollama_list, but the Gemini-specific focus provides some distinction. The purpose is specific enough for a list operation.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (like authentication), timing (when model availability matters), or relationships to sibling tools (like mcp_gemini_chat_completion which would need a model). There's no explicit 'when' or 'when not' context provided.

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