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

No annotations, so the description carries the burden, and it does disclose the return fields (id, type, minimum VRAM, parameter scale) plus the alias-matching quirk. It does not state that the operation is read-only or how results are capped, leaving some gaps.

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?

Three short sentences with no filler; the core action and the aliasing caveat are front-loaded before the return-value summary.

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 three-parameter read tool with no output schema, listing the returned fields makes it actionable. Missing only minor details such as the interaction between limit and the full listing 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?

Schema coverage is 67%, and the description's query explanation largely repeats the schema's own text. The alias example (Qwen3.8 27B / qwen3.8-27b) adds real value, but type and limit receive no treatment in the description.

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?

Specific verb plus resource ('按名字或类型查找模型 ID') with an example of the alias matching behavior. It clearly separates itself from the sibling model_requirements by framing this as the ID-confirmation step.

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?

Explicitly tells the agent to call this before checking VRAM requirements, and states that omitting the query lists all models. It routes to the right workflow but doesn't explicitly name the alternative tool or cover when to filter by type instead.

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