get_law_tree

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

With no annotations, the description carries the full burden. It explains the output includes article ranges and counts, and that it extracts from law JSON with a specific header. However, it does not mention auth requirements, rate limits, or potential size limitations for large trees. Minor omission but overall transparent.

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 concise: a few sentences each serving a purpose. It front-loads the core function, then differentiates from siblings, and ends with usage suggestions. No redundant or wasted words.

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 no output schema, the description adequately describes the output (structure with article ranges and count). It explains all three parameters, provides a concrete use case, and references related tools. It is complete for a tree/toc 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 coverage is 100% with descriptions, so baseline is 3. The description adds value by clarifying that mst and lawId are alternatives (택1) and efYd is for time-point queries. This extra context justifies a 4.

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 extracts the internal table of contents (편·장·절·관) of a law, including article ranges and counts. It distinguishes itself from get_law_text (full text) and get_law_system_tree (hierarchy of laws), making the purpose unambiguous.

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 explicitly says when to use this tool: for navigating large laws like PIPA to quickly decide which chapter/section to examine. It also tells when not to use it (for full text or system hierarchy) and suggests follow-up tools (get_law_text, compare_articles). This is exceptional guidance.

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