mcp_ollama_run

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

No annotations are provided, so the description carries full burden. It mentions running a model to generate a response, implying a read-only operation, but lacks details on behavioral traits like rate limits, error handling, authentication needs, or what the response format looks like. This is inadequate for a tool with potential complexity.

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 without any wasted words. It is appropriately sized and front-loaded, making it easy to parse 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 no annotations and no output schema, the description is incomplete. It fails to address key contextual aspects like the response format, error conditions, or how it differs from similar sibling tools (e.g., 'mcp_ollama_chat_completion'), leaving significant gaps for an AI agent to understand its full behavior.

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 clear descriptions for all parameters (name, prompt, timeout). The description adds no additional meaning beyond the schema, such as examples or constraints, so it meets the baseline of 3 where the schema does the heavy lifting.

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 action ('실행하여 응답을 생성합니다' - run to generate a response) and resource ('Ollama 모델' - Ollama model), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'mcp_ollama_chat_completion' which likely serves a similar purpose, preventing a perfect score.

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. With multiple sibling tools for model interactions (e.g., 'mcp_ollama_chat_completion', 'mcp_gemini_generate_text'), there's no indication of specific contexts, prerequisites, or exclusions for this tool's use.

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