law_josub

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety aspects. The description adds valuable context: it specifies the tool returns 'only the requested article/paragraph' (scoping behavior), notes 'JSON not supported by API' (limitation), and provides format defaults ('default "XML"'). This goes beyond annotations without contradicting them.

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 well-structured with clear sections (purpose, args, returns, examples) and uses bold for emphasis. It's slightly verbose but every sentence adds value: the purpose statement, parameter explanations, and examples are all necessary given the complex parameter formatting. Minor redundancy in examples keeps it practical.

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?

For a tool with 8 parameters, 0% schema coverage, no output schema, and complex formatting requirements, the description is highly complete. It covers purpose, usage context, all parameter semantics, behavioral notes (e.g., format limitations), and provides concrete examples. Given the annotations handle safety, this description fills all remaining gaps 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?

With 0% schema description coverage, the description fully compensates by explaining all 8 parameters. It clarifies required conditions ('either id or mst is required'), provides detailed formatting rules for jo, hang, ho, and mok with examples, explains defaults for oc and type, and notes constraints like 'JSON not supported.' This adds significant meaning beyond the bare 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 the tool's purpose: 'Query specific article/paragraph by announcement date' and explicitly positions it as 'BEST TOOL for querying specific articles like "제174조", "제3조" etc.' It distinguishes from siblings by noting it 'returns only the requested article/paragraph, avoiding large full-law responses,' which differentiates it from broader search tools in the sibling list.

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 provides explicit usage guidance: it states this is the 'BEST TOOL for querying specific articles' and contrasts it with 'avoiding large full-law responses,' implying alternatives like law_search or law_service for broader queries. It also includes practical examples showing when to use specific parameters.

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