Taiwan Legislative Yuan 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. It mentions the return format (JSON) and error handling (Chinese error messages), which is helpful. However, it doesn't describe pagination behavior beyond default values, rate limits, authentication requirements, or whether this is a read-only operation.

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 reasonably structured with sections for Args, Returns, and Raises, but it wastes space by duplicating parameter documentation already present in the schema. The initial purpose statement is too brief, and the parameter section could be more concise given the schema coverage.

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 9-parameter list tool with no annotations but 100% schema coverage and an output schema, the description provides basic purpose and return format information. However, it lacks crucial context about filtering logic, pagination details, and differentiation from sibling tools, making it incomplete for optimal agent usage.

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 already documents all parameters thoroughly. The description repeats the parameter information but adds no additional semantic context about how parameters interact, which combinations are meaningful, or filtering logic. 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 as '列出法條資料' (list law contents), which is a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'get_law_content' or explain how listing differs from getting individual law content, which prevents 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 like 'get_law_content' or 'list_laws'. It doesn't mention prerequisites, use cases, or any contextual factors that would help an agent choose between this and its many sibling tools.

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