agy_models

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It conveys a read-only query action ('查询'), which is useful, but it does not mention response format, pagination, ordering, rate limits, or authorization needs. This is minimally transparent but not richly 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?

The description is a single sentence that immediately states the tool's action and target resource. There is no filler, and the essential 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?

Given the low complexity (no parameters, no output schema) and clear purpose, the description is largely sufficient for an agent to invoke the tool correctly. The only minor gap is the absence of any detail about the returned list contents or behavioral guarantees, but this is not critical for a simple model-list query.

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 input schema is empty (0 parameters), and the baseline for zero-parameter tools is 4. The description adds no parameter-specific detail because none is needed; there is nothing beyond the schema for the agent to disambiguate.

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 ('查询') and resource ('Antigravity 可用的 AI 模型列表'), clearly stating that the tool lists available AI models. This distinguishes it from the sibling tools agy_prompt and agy_conversation, which appear to handle prompt and conversation tasks rather than model listing.

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 implies usage: call this tool when you need to see available AI models on Antigravity. However, it does not explicitly state when not to use it, nor does it mention any alternative tool or edge cases, so the guidance remains implicit rather than explicit.

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