Return the full text of an entire Taiwan law (all articles, with chapter/section headings), formatted as Markdown. For a single article prefer get_article_by_number; use this when you need the whole statute. The law counterpart of get_decision_details.
| Name | Required | Description | Default |
|---|---|---|---|
| law_name | Yes | Exact law name in Traditional Chinese, e.g. "公司法". Use search_law_titles first if you only have a partial or informal name. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful context the annotations do not: the returned payload is Markdown including chapter/section headings. It does not mention auth or any truncation/size limits for very large statutes, which is the only real gap.
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?
Three tight sentences, no filler: capability and return format first, then the disambiguation rule, then a one-line sibling analogy. Every sentence earns its place and the most important routing info is front-loaded.
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 single-parameter read tool with no output schema, the description supplies the missing return-shape information (full statute as Markdown with headings) and full sibling routing, while annotations carry the safety profile. An agent has everything needed to call it 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?
Schema coverage is 100% and the single law_name parameter is fully documented in the schema, including the Traditional Chinese requirement and the search_law_titles fallback. The description adds no parameter detail beyond that, so the baseline of 3 applies.
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?
States a precise verb and resource (return full text of an entire Taiwan law) plus scope (all articles, chapter/section headings) and output format (Markdown). It differentiates itself from siblings by naming get_article_by_number and get_decision_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?
Explicit routing: 'For a single article prefer get_article_by_number; use this when you need the whole statute.' It names the alternative and the condition that selects it, leaving nothing to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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