列出可用生成模型

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

With no annotations provided, the description bears the full burden of behavioral disclosure. It explains the output fields 'available', 'price', and 'group_ratios' and their interpretations (e.g., 'available=true' means directly callable). This provides sufficient transparency for a read-only listing tool, though it omits details on pagination or error handling.

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, front-loaded paragraph that states the core function first. It is concise with no redundant sentences, but the explanations of 'available', 'price', and 'group_ratios' could be slightly more integrated. Overall, it is well-structured for quick comprehension.

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 absence of an output schema, the description covers the key response fields (available, price, group_ratios) and filtering capabilities. It does not mention pagination or response format details, but for a listing tool with 3 optional parameters and simple logic, it provides adequate context for an agent to use it correctly.

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?

Since schema coverage is 100%, the baseline is 3. The description adds minimal extra meaning beyond the schema: it repeats the filtering concept and explains 'available' (which is not a parameter). The keyword param's description in the schema is already clear, and the description does not provide new formatting or constraints.

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 clearly states '列出可用生成模型' (list available generation models) and specifies the supported media types (图像/视频/音频/文档). It distinguishes itself from sibling generation tools like generate_image by focusing on discovery rather than creation, and explicitly mentions filtering by media_type or keyword, leaving no ambiguity about the tool's purpose.

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 context by explaining the 'available' field's meaning (directly callable vs. not provisioned), which helps agents decide which model to use for generation tasks. However, it lacks explicit guidance on when to use this tool versus alternatives like analyze_media or get_task, and does not specify prerequisites or exclusions.

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