get_law_abbreviations

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

With no annotations, the description fully discloses caching behavior (24-hour cache, bypassCache flag), server-side date filtering (stdDt/endDt), large response size (1.2MB+), and automatic domain abbreviation conversion. No contradictions exist.

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 for its content, front-loading the purpose. It could be slightly more structured but every sentence adds value.

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 explains return values (bidirectional mapping) and covers all behavioral aspects (caching, filtering, domain aliases). The tool's complexity is well-addressed.

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?

Although schema coverage is 100% (baseline 3), the description adds significant meaning: stdDt/endDt filter on server side ignoring cache, bypassCache forces refresh, display is client-side truncation, and omitting query dumps items. This greatly aids parameter understanding.

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 is a law abbreviation dictionary from the Ministry of Legislation, performing partial matching on queries. It distinguishes itself from siblings by mentioning domain-specific abbreviation handling (e.g., '정통망법' via PRIVACY_ALIASES) and bidirectional mapping between abbreviations and full names.

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?

It explicitly describes when to use this tool (for abbreviation lookups) and contrasts it with get_law_text(mst) for full text and search_law(query) for formal search. Examples are provided to illustrate usage.

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