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

Annotations already declare the operation as read-only, idempotent, and non-destructive. The description adds useful context by specifying the returned fields (ID, name, type, visibility) and 'current' state, which goes beyond the annotation metadata. No contradictions.

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, well-structured sentence that immediately states the tool's action and output contents. There is no wasted text or redundancy with the annotations.

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 list tool with no output schema, the description adequately conveys what is returned (ID, name, type, visibility) and that it reflects the current state. The robust annotations cover safety, making the description sufficient, though it could optionally mention the return type (e.g., array) or empty behavior.

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?

There are zero parameters, and schema coverage is trivially 100%. With no parameters to explain, the description does not need to add parameter semantics; the baseline score of 4 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 '获取' (get) and identifies the resource '所有图层列表' (all layers list), specifying the included fields (ID, name, type, visibility). This clearly distinguishes it from sibling tools that add, update, or remove layers.

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 clear context—it lists all current layers—but gives no explicit guidance on when to use it versus alternatives, nor any exclusions. The use case is implied via its sibling tools, but no direct comparison is made.

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