analyze_food_image

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

With no annotations provided, the description must carry the full burden of behavioral transparency. It states what the tool returns, but it does not disclose potential side effects, error conditions (e.g., invalid URL, non-food image), or whether any external network requests are made. The description is adequate but not rich in behavioral detail.

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, focused sentence that front-loads the main purpose and immediately lists expected outputs. Every word contributes to clarity, with no wasted or redundant content. It is an excellent example of concise tool documentation.

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 simplicity of the tool (one parameter, no output schema, no annotations), the description provides adequate context: it identifies the input and describes the output categories. It lacks explicit differentiation from the sibling tool, but this is more a usage-guideline gap than a completeness issue. The description is sufficiently complete for a straightforward analysis tool.

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 single parameter 'image_url' is already well-documented in the schema with a clear description ('Public URL of a food image to analyze'). The tool description adds no additional semantic information beyond what the schema provides, so it remains at the baseline for a fully documented parameter.

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: analyzing a food image URL and returning detailed nutritional information. It enumerates specific outputs (calories, macros, vitamins, minerals, allergens, dietary flags), making the purpose unambiguous. The resource (food image URL) distinguishes it from the sibling 'analyze_food', which likely handles non-image food data.

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 when the user has a food image URL, but it does not explicitly state when to use this tool versus the sibling 'analyze_food' or any alternatives. There are no clear exclusions or scenario-based guidance, so the usage context is only implied rather than explicitly articulated.

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