Taiwan Legislative Yuan MCP Server

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns JSON-formatted detailed information and raises exceptions with Chinese error messages, which adds useful behavioral context beyond the input schema. However, it doesn't cover other traits like rate limits, authentication needs, or whether it's read-only (implied but not stated).

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 appropriately sized and front-loaded with the purpose in the first sentence. The Args, Returns, and Raises sections are structured clearly, though the Args section repeats schema information. Every sentence earns its place by providing essential details, but minor redundancy reduces efficiency.

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 tool's complexity (single parameter, read-like operation) and the presence of an output schema (implied by 'Returns: str: JSON 格式'), the description is mostly complete. It covers purpose, parameter, return format, and error handling. However, without annotations, it could benefit from more behavioral context like read-only confirmation or usage prerequisites.

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 the schema already fully documents the single parameter 'law_content_id' with an example. The description repeats this example in the Args section but doesn't add meaning beyond what's in the schema, such as explaining the format components or where to obtain the ID. Baseline 3 is appropriate when 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 purpose: '取得特定法條的詳細資訊' (get detailed information for a specific law article). It specifies the resource (law article) and verb (get detailed information), making it distinct from siblings like 'get_law' or 'list_law_contents'. However, it doesn't explicitly differentiate from 'get_law_versions' or 'get_law_progress', which might also retrieve law-related details.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention siblings like 'get_law' (which might retrieve law metadata) or 'list_law_contents' (which might list multiple law articles), leaving the agent to infer usage from tool names alone. There's no explicit context or exclusions stated.

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