article_citation

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 and idempotency. The description adds valuable behavioral context beyond annotations: it specifies the data source ('parses official hyperlinked citations from law.go.kr HTML pages'), accuracy claims ('100% accurate citation data'), and cost implications ('zero API cost'). It also describes what types of citations are identified (external, internal, article/paragraph/item level).

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 statement, what it identifies, args, returns, examples, and workflow. Most sentences earn their place by providing essential information. There's some redundancy (the Korean title '조문 인용 조회' appears twice, and the workflow section partially repeats earlier guidance), but overall it's efficiently organized with front-loaded key information.

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 the tool's complexity (5 parameters, 0% schema coverage, no output schema), the description provides comprehensive context. It fully explains all parameters with examples, describes the return structure in detail (including all fields like success, law_id, citations, internal_count, etc.), provides concrete usage examples, and integrates this tool into a broader workflow with sibling tools. This compensates for the lack of structured output schema.

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 carries the full burden of explaining parameters. It provides clear semantic explanations for mst ('Law MST code - get this from eflaw_search or law_search results'), law_name ('Law name in Korean'), article ('Article number'), article_branch ('Article branch number'), and oc ('Optional OC override'). It includes examples showing how to use article_branch for special cases like '제37조의2'. The only minor gap is that oc's purpose could be more explicitly explained.

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 specific action ('extract citations'), target resource ('from a law article'), and scope ('all legal citations referenced by a specific law article'). It explicitly distinguishes this tool's function from sibling tools like eflaw_search (which finds laws) and eflaw_service (which gets article text), establishing clear differentiation.

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 workflow guidance: 'First use eflaw_search... to find the law and get MST, then use article_citation... to get citations, optionally use eflaw_service to get the full article text.' This clearly defines when to use this tool versus alternatives and establishes prerequisites, with concrete examples showing the sequence.

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