get_law_text

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

Discloses truncation limit of 12,000 characters and use of efYd for time-specific versions. No annotations provided, so burden is on description; it could mention error cases or response format but is otherwise 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?

Concise three sentences, front-loaded main purpose, then behavioral details and usage guidance. No unnecessary 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?

No output schema, so description must compensate. It notes results are sorted by article (조문 단위로 정렬됨) and mentions truncation. Could be more detailed on return structure, but is sufficient for context.

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% so baseline is 3. Description adds value by explaining mutual exclusivity of mst and lawId (택1) and clarifying efYd's role for versioned queries, going beyond schema.

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 it retrieves the full text of a law using mst or lawId, returned sorted by article. It distinguishes from sibling tools like get_law_article for specific articles, and mentions related tools for history and relationships.

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?

Explicitly says when to use this tool (for full law text) and when not (for large laws truncated at 12,000 characters, recommending get_law_article for specific articles). Also suggests next steps: get_related_laws and get_law_history.

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