analyze_image

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

With no annotations provided, the description must fully disclose behavioral traits. It states that the tool uses a vision-capable LLM and returns a textual description, but it does not mention potential side effects, network requirements, or that the image is not modified. The description provides essential but minimal behavioral information.

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, well-structured sentence that conveys the tool's purpose without any superfluous words. It is concise and front-loaded, making it easy for an agent to quickly grasp the core function.

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?

The description covers the fundamental purpose but leaves gaps in parameter guidance and usage scenarios. The output schema exists, so return values are handled, but the tool's three parameters and potential configurable behavior are not explained. For a relatively simple tool, it is adequate but not complete.

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 description coverage is 0%, and the description does not explain the parameters. It implies that 'image_path' refers to a local image file, but the 'model' and 'prompt' parameters are completely unaddressed. This is a significant gap because the description fails to compensate for the lack of schema documentation.

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 function: it 'Analyzes local images or screenshots using a vision-capable LLM and returns a detailed textual description.' This provides a specific verb (analyzes), resource (local images/screenshots), and outcome, which is unambiguous and distinguishes it from any potential alternatives.

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 gives clear context for when to use the tool: when you need to analyze a local image or screenshot and get a textual description. It does not exclude any specific cases, and with no sibling tools, explicit alternatives are not needed. However, it lacks guidance on prerequisites or when this tool would be inappropriate.

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