list_connections

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

No annotations are provided, so the description carries the transparency burden. It conveys read-only intent ('조회') and the output content, but does not address prerequisites, error behavior, or whether the list is complete or ordered. For a simple non-mutating list this is adequate but not detailed.

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?

Two sentences: the first states the result, the second gives the user-interaction usage rule. No filler, and the key information is front-loaded.

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 parameterless listing tool, the description covers what it returns and when to use it. It could add a note on output shape/ordering or side-effect safety, but no output schema exists, so the description is nearly complete.

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 tool has zero parameters and the schema documents this with 100% coverage, so there is no parameter meaning for the description to add. Baseline 4 applies.

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?

Description states a specific action ('retrieves list of registered DB connections') and the returned content ('numbers and aliases'). This clearly differentiates it from sibling query/write/test tools that operate on an already-chosen connection.

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?

It gives an explicit trigger: when the target DB is ambiguous, show the list to the user and ask them to pick a number. However, it does not name sibling tools or state when not to use it, so it is not a complete routing guide.

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