article_citation

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds that it parses HTML pages from law.go.kr, implying a web-scraping mechanism that could be fragile. It also claims '100% accurate citation data with zero API cost,' which is useful operational context. However, it does not disclose potential rate limits or failure modes of scraping, so it doesn't fully cover behavioral risks.

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 (Args, Returns, Examples, Workflow) and is appropriately sized for the tool's complexity. It front-loads the purpose and uses concise bullet-like formatting. Each sentence adds value, including practical examples and workflow guidance.

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 fully explains return values including success, law_id, law_name, article, citation_count, citations, internal_count, and external_count. It also provides two complete usage examples and a workflow that integrates with sibling tools. For a tool of this complexity, the description is comprehensive.

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 has no parameter descriptions (0% coverage), so the description must explain all parameters. It does so thoroughly: mst is defined as Law MST code with guidance to get from search results, law_name with a Korean example, article with example '3 for 제3조', article_branch with default 0 and example '2 for 제37조의2', and oc as an optional override defaulting to env var. This exceeds basic schema information.

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 function: 'Extract citations from a law article' and specifies it extracts all legal citations referenced by a specific law article. It distinguishes from siblings by detailing the scraping of official hyperlinked citations from law.go.kr HTML pages and listing internal/external citation types, making it unique among the many search/service tools.

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 an explicit workflow: 'First use eflaw_search... Then use article_citation... Optionally use eflaw_service to get the full article text.' It also tells users where to get the mst parameter ('get this from eflaw_search or law_search results'), clearly situating this tool relative to alternatives.

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