ncloud_get_postgresql_image_products

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

The readOnlyHint annotation already communicates safety. The description adds value by specifying that it lists 'image product codes (engine versions)', clarifying the exact output scope. No contradiction exists between the description and annotations.

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, front-loaded sentence with no unnecessary words. It immediately states the verb and resource, making it concise and easy to parse.

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 simple read-only listing tool with one optional parameter and no output schema, the description adequately conveys the tool's purpose and output. It could mention the optional regionCode behavior, but the schema covers that, leaving little else needed.

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 description coverage is 100% (regionCode is described with valid values). The description adds no extra parameter details, but the schema fully documents the only parameter, 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 clearly states the action (List), the resource (available Cloud DB for PostgreSQL image product codes), and the purpose (engine versions). It distinguishes itself from sibling tools like ncloud_get_postgresql_products and other get_*_image_products tools by specifying the PostgreSQL engine and image product scope.

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 makes it clear this tool lists PostgreSQL image product codes, which implies it is used when you need engine versions for PostgreSQL. It does not explicitly mention alternatives or when not to use it, but the name and description provide sufficient context for an AI agent to select it over other image product tools.

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