Gemini MCP Server

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. While it states the tool generates text, it doesn't describe important behavioral traits such as rate limits, authentication requirements, potential costs, response formats, or error conditions. For a text generation tool with 5 parameters and no annotations, this represents a significant gap in 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 extremely concise with just two sentences that directly communicate the core functionality and use cases. Every word earns its place, and the information is front-loaded with the primary purpose stated immediately. No unnecessary elaboration or redundancy exists.

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 complexity of a text generation tool with 5 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns, how to interpret results, error handling, or important behavioral constraints. The agent would need to guess about the output format and operational characteristics.

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 schema description coverage is 100%, so all parameters are documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema. According to guidelines, when schema coverage is high (>80%), the baseline score is 3 even with no parameter information in the description.

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 as '텍스트를 생성합니다' (generates text) and provides specific use cases like summarization, translation, and creation. This distinguishes it from sibling tools (analyze_code, analyze_image, analyze_pdf) which are for analysis rather than generation. However, it doesn't explicitly differentiate from potential text-generation alternatives within the same domain.

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 contexts ('요약, 번역, 창작 등에 활용할 수 있습니다' - can be used for summarization, translation, creation, etc.) but doesn't provide explicit guidance on when to use this tool versus alternatives. No exclusions or prerequisites are mentioned, leaving the agent to infer appropriate usage scenarios.

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