lunaar_food_visual

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

No annotations are provided, so the description bears full responsibility for disclosing behavior. It states the AI analyzes the meal, adapts the environment, and never redesigns the meal itself. It also notes credit cost and latency. However, it does not clarify if the operation is read-only or destructive, nor does it describe the output format or how the result is returned.

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 three sentences, efficiently covering purpose, mood options, and key constraints. No redundant or extraneous information is present. It is well-structured and front-loaded with the main action.

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 moderate complexity (six moods, three parameters) and lack of output schema, the description covers purpose, parameters, cost, and latency. However, it omits the output format (e.g., image URL or base64) and how the result is accessed, which would be valuable for an AI agent. Overall, it is fairly complete but could include return value details.

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 description adds significant meaning beyond the input schema. Each mood value is explicitly described (e.g., 'studio=white background menu shot'), and constraints for imagePath (format and size) and aspectRatio (defaults to auto) are provided. The schema covers 67% of parameters with descriptions, but the description enriches understanding of all three parameters.

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: turning a casual food photo into a premium food photograph. It is distinct from sibling tools (e.g., lunaar_jewelry_tryon, lunaar_product_shot) by focusing specifically on food images. The six mood options are detailed, making the tool's capability unambiguous.

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 usage context (list of moods and their styles) but does not explicitly specify when to use this tool versus alternatives. It lacks when-not conditions or direct comparisons to siblings. The credit cost and latency are mentioned, which aids selection, but overall guidance is implicit.

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