Gp Rename Dataset

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true, so the safety profile is covered structurally. The description adds a modest amount of context by flagging that write and path restrictions depend on service capabilities, but it omits important mutation semantics — whether the source dataset survives, whether the rename is atomic, and what happens on name collisions or locked data.

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 short sentences with the core action front-loaded and no padding. The trailing clause about 'verifiable structured results' is generic boilerplate, but the description is well within a reasonable size.

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?

An output schema exists, so return values need not be described, but for a mutation tool with two completely undocumented parameters and no sibling differentiation the description is too thin. An agent cannot determine from this text alone what valid inputs look like or how this differs from rename_layer, rename_map, and rename_layout.

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 0% for both required parameters (in_data, out_data), so the description carries the full burden of explaining them — and it says nothing. It does not clarify whether inputs are full catalog paths, dataset names, or workspace-relative, nor whether the output must be in the same workspace as the input.

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 states a specific verb and resource ('重命名数据集' / rename dataset), which is clear enough for an agent to know what the tool does. It does not, however, differentiate itself from the many sibling rename operations (rename_layer, rename_map, rename_layout) or from dataset-level tools like delete_dataset, so an agent must infer that this operates on a workspace dataset rather than a project object.

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?

There is no statement of when to use this tool versus alternatives, no prerequisites, and no mention of required context such as an open project or a workspace path. The only guidance-like clause ('写入和路径限制以服务能力为准') is a vague disclaimer about service capabilities, not an actionable condition for tool selection.

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