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

With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates a read operation returning a list, implying no side effects, but it does not mention any details such as pagination, sorting, or potential empty results. This is acceptable for a simple listing tool but lacks explicit transparency.

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, concise Korean sentence that is front-loaded with the action and resource. It contains no filler or redundant information, perfectly matching the tool's simple purpose.

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?

The description is minimal and lacks details about the return value structure (e.g., what fields each mock server object contains) since there is no output schema. For a simple list tool, this is adequate but not fully complete; an agent might need more context to interpret the returned list correctly.

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 and schema coverage is trivially 100%. Baseline for 0 params is 4, as there are no parameter semantics to clarify. The description correctly omits parameter information since none exist.

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 uses a specific verb '반환합니다' (returns) with a clear resource '생성된 모든 목업 서버 목록' (list of all created mock servers). It explicitly mentions 'all' which distinguishes it from sibling tools like get_mock_endpoint that likely return a single mock, thus providing clear purpose and sibling differentiation.

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: call this tool when you need the full list of mock servers. However, it does not explicitly state when to prefer this over alternatives or provide any exclusions, so the guidance is only implied.

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