generate_web_image

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the API (DashScope) and model (FLUX) but fails to disclose critical traits like rate limits, costs, authentication requirements beyond the apiKey parameter, error handling, or output format. This leaves significant gaps for an AI agent to understand operational constraints.

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 concise and well-structured in two sentences: the first states the core purpose, and the second provides usage examples. Every sentence adds value without redundancy, making it efficient and front-loaded with key information.

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's complexity (AI image generation with 5 parameters) and lack of annotations and output schema, the description is incomplete. It doesn't explain the return value (e.g., image file, URL, or error details), performance expectations, or limitations, leaving the agent with insufficient context to use the tool effectively.

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 has 100% description coverage, documenting all 5 parameters thoroughly. The description adds no additional parameter semantics beyond what the schema provides, such as explaining relationships between parameters or usage nuances. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.

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 the tool's purpose: 'Generate AI images for web design using FLUX model via DashScope API.' It specifies the action (generate), resource (AI images), and context (web design). However, with no sibling tools, it cannot demonstrate differentiation from alternatives, preventing a perfect score.

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 provides implied usage context by listing examples ('placeholder images, hero images, product images, and other web assets'), which suggests when to use it. However, it lacks explicit guidance on when not to use it or alternatives, and there are no sibling tools to compare against, so the guidance is incomplete.

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