quick_stats

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

No annotations are provided, so the description must cover behavioral traits fully. It discloses the result format ('2024년 서울의 실업률은 3.2%입니다') and supported data types, but does not mention error handling, rate limits, or side effects. While sufficient for a read-only tool, it lacks depth.

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 sections, bullet points, and examples, making it easy to scan. However, it is slightly verbose, containing redundant clarifications (e.g., repeated emphasis on keyword extraction). Overall, it earns its length but could be more concise.

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 six parameters, no output schema, and seven sibling tools, the description is very complete. It covers query construction, region handling, time periods, and provides a sample output. It lacks detailed return field documentation, but the example output compensates. The agent has enough context to use the tool 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 detailed parameter descriptions, but the description adds substantial meaning beyond the schema: it explains keyword extraction rules (e.g., dropping 감소/증가), enumerates supported keywords (90+), lists 17 regions, and provides usage examples for compound queries. This significantly aids correct parameter selection.

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 explicitly states '한국 통계 수치를 즉시 반환합니다' (returns Korean statistical figures immediately), which is a specific verb+resource. It also distinguishes itself from siblings like analyze_time_series, compare_statistics, etc., by focusing on quick retrieval of static values rather than analysis or comparison.

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 triggers (e.g., '~얼마야?', '~알려줘') and gives rules for extracting keywords (e.g., removing modifiers like 감소/증가). It includes multiple examples showing when to use the tool and how to format queries, making it clear for the agent.

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