cubism_get_parameters

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

With no annotations provided, the description bears full burden. It correctly implies a read operation ('获取') and describes the data returned, but does not explicitly state read-only behavior, authorization needs, or side effects. Given the output schema exists, the description is sufficient but lacks explicit safety traits.

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 extremely concise: one sentence for purpose, one for differentiation, one bullet for the parameter. No wasted words, front-loaded with the core action.

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?

Given the tool has an output schema, it does not need to describe return values. The description covers input parameter semantics and differentiation from a key sibling. It could mention usage contexts like when detailed parameter structure is needed, but is mostly 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?

Schema coverage is 0% (no parameter descriptions in schema), so the description compensates by adding an Args section explaining model_uid as '模型 UID'. This adds meaning beyond the bare schema. With only one parameter and clear explanation, it helps the agent.

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 it gets detailed metadata of model parameters including type, range, default, key points, blend shapes, loops. It explicitly distinguishes itself from cubism_get_parameter_values by noting it returns additional structural information like parameter names, types, ranges, GroupUID.

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 directly compares with cubism_get_parameter_values, clearly indicating when to use this tool for richer metadata. However, it does not explicitly state when not to use it or mention other alternatives.

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