doubao_vision_understand

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

With no annotations, the description carries the full burden. It does not disclose authentication needs, rate limits, failure behaviors (e.g., invalid image), or the response format. Minimal behavioral information is provided beyond the basic API call.

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?

Two concise sentences with no wasted words. Information is front-loaded and efficiently communicates the core functionality and configuration option.

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?

Missing output schema and behavioral details. The description does not explain what the tool returns or how to interpret results. For a vision analysis tool with multiple parameters, more context is needed for completeness.

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 100%, so baseline is 3. The description adds little beyond the schema: it mentions image can be file path or URL and prompt specificity, but these are already in schema descriptions. The description does not explain how parameters interact or provide additional context.

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: 'Analyze an image using Doubao vision model via Volcengine Ark API.' It mentions both preset and custom inference modes, providing good specificity. However, 'analyze' is somewhat broad, and without sibling tools, differentiation isn't needed.

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?

No guidance on when to use this tool versus alternatives. It mentions configuration via environment variable as a prerequisite, but lacks context for optimal use cases or exclusions.

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