search_law

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

Annotations already mark readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds significant behavioral details: automatic fallback, abbreviation conversion, concurrent listing of title changes and amendments. No contradictions.

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 somewhat long but tightly packed with useful information. It is front-loaded with the core purpose, and each sentence adds value. Could be slightly more concise, but structure is good.

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?

With no output schema, the description mentions the return of lawId and mst but not full structure. However, annotations (readOnlyHint, openWorldHint) and the detailed purpose make it complete enough for an agent to use effectively.

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 for both parameters. The description adds example query values and a note on the display parameter, but the schema already covers meaning adequately. Baseline 3 is appropriate.

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 searches Korean law names, ordinance names, and administrative rule names by keyword to obtain lawId and mst. It distinguishes from siblings by focusing on identifier acquisition for subsequent queries.

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 explains use cases (acquiring identifiers before text queries) and includes fallback behavior (auto-fallback to local ordinances/rules on zero results). It lacks explicit exclusions or alternatives but provides clear context.

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