Analyze Meal

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

Annotations already indicate read-only and idempotent hints. The description adds key behaviors: resolves items in one call, returns macro totals plus target comparison, renders visual nutrition label in supported clients, and recognizes diverse input formats (counts, weights, fractions, sizes). No contradictions.

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 front-loaded with the key value proposition and uses clear, purposeful sentences. The Japanese version is a minor redundancy but still efficient.

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 no output schema, the description adequately explains what is returned (macro totals, target comparison, visual label). It covers input format thoroughly. Slight gap on explicit return structure, but sufficient for a read-only 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?

Schema coverage is 100% with descriptions for both parameters. The description enhances by providing concrete examples (e.g., '1 oikos plain', '200g rice') and explaining recognition capabilities, adding value beyond the schema.

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: analyzing a whole meal (two or more items) in one call, returning macro totals and target comparison. It distinguishes from sibling tools like konbini_item, restaurant_meal, and search_food, which is explicit and effective.

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 explicitly states when to use this tool ('whenever the user describes a whole meal') and when not to ('Do NOT decompose a meal into separate... lookups'). It also advises on passing user_profile for personalized targets.

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