query_regulation

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

With no annotations, the description carries the full burden and does so well: it discloses the 50-article cap, that overflow returns has_more plus a continuation point, that non-existent requested articles appear under missing, that omitting article_no yields structure (headings and article-number ranges) rather than text, and that English translations frequently lag Chinese amendments. Behavioral traits are disclosed far beyond a bare parameter list.

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?

Front-loaded with the core retrieval behavior before the arg list, and each section earns its place. There is mild redundancy between the Args and Returns blocks (article_history and history are each explained twice), which keeps it from the top mark.

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?

Despite no output schema, the description fully specifies the return shape: law (pcode, name, status, plus last_amended, category, effective_date/effective_note), articles, source_url, and the optional history and article_history fields. Together with the documented edge cases, an agent has everything needed to call and interpret this 7-parameter tool.

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 0%, so the description must compensate entirely, and it does: law_name is noted as auto-converted to pcode, pcode's format is exemplified ('B0000001'), article_no's three accepted syntaxes are shown with real values ('184', '184~198', '184,185,247-1'), from_no/to_no are defined as an equivalent range form, and include_history/language carry their own semantics.

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 specific verb and resource (retrieve articles from the national regulations database) and enumerates the supported granularities: single article, range, cross-number multiple. However, it never distinguishes itself from the closely-named sibling search_regulations, so an agent must infer which one finds laws versus reads articles.

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?

Gives explicit when-conditions: omit article_no to get only the chapter/article index first, then specify article_no to read text; set include_history=True when the user asks about amendment history; check effective_date/effective_note before citing newly amended articles; use language='en' for English versions. It stops short of naming any alternative tool or when-not-to-use-this-tool case.

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