테이블 구조

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

The description adds value beyond the readOnlyHint annotation by enumerating the exact metadata returned (columns, data types, NULL allowance, defaults, primary key). It is consistent with the annotation and gives the agent clear expectations of output content.

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 a single, focused sentence with no redundancy. It front-loads the core action and lists all relevant output aspects without unnecessary words.

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 low-complexity metadata inspection tool, the description plus schema and readOnlyHint are sufficient. It covers purpose, input, output content, and safety; no output schema is necessary because the description already specifies the return fields.

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?

The input schema already provides complete descriptions for both parameters (table name, schema name) at 100% coverage. The description does not add parameter-level detail, but the schema carries the burden effectively, so a baseline score of 3 is appropriate.

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 uses a specific verb ('조회합니다' / retrieves) and identifies the exact resource: table columns, data types, nullability, defaults, and primary key. This clearly distinguishes it from siblings like list_tables (listing tables) and query (querying data).

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 usage context is implied: use this when you need table schema metadata rather than table names or actual data. However, it does not explicitly state when to use this tool over alternatives, nor does it mention any exclusions or prerequisites.

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