Estimate meal photo

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds behavioral context beyond annotations: it clarifies that the tool requires user confirmation before logging, and that it operates on an 'agent-provided photo observation' (meaning the agent must provide a text description of a photo). This is consistent with annotations and adds value.

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 very concise at one sentence, which is good for brevity. However, it lacks structure (no bullet points, sections, or parameter overview). For a tool with five parameters and a complex input schema, the conciseness comes at the cost of omitted parameter details and usage examples.

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 five parameters, no output schema, and 0% schema coverage, the description is insufficient. It does not explain the return format, how to construct the 'detected_items' array, or the role of 'response_format'. While it mentions the confirmation requirement, it lacks completeness for effective tool usage. The tool interacts with meal logging, but the description doesn't connect to related logging tools.

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%, meaning none of the five parameters have descriptions. The description does not elaborate on any parameter, even though it's the primary source of semantic information. For instance, 'image_description' is required but not explained; 'detected_items' is a complex array with no guidance; 'locale' and 'meal_type' have defaults but no purpose. This severely hinders correct parameter usage.

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: 'Estimate meal nutrition from an agent-provided photo observation'. It specifies the verb ('estimate'), the resource ('meal nutrition from photo'), and includes a critical constraint ('always requires user confirmation before logging'). This differentiates it from sibling tools like nourish_estimate_meal (which likely uses manual input) and nourish_analyze_food_image (which might analyze without full estimation).

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 explicit guidance on when to use this tool: it requires user confirmation before logging. This is a strong usage guideline. However, it does not mention alternatives or when not to use it, such as preferring nourish_estimate_meal for non-photo inputs or nourish_analyze_food_image for just analysis. The confirmation requirement is clear and helpful.

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