foodish_by_category

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

Annotations already declare readOnlyHint and openWorldHint, and the description adds nothing about the response shape (image URL vs binary), pagination, or failure behavior for unknown categories. Worse, 'random' implies a different result on each call, which sits awkwardly against idempotentHint=true.

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?

One sentence, front-loaded with the verb and the random-scoping that matters, with no filler. It is terse to the point of omitting sibling routing, but nothing is wasted.

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?

For a single-parameter read-only lookup with annotations and no output schema, the core information is present. What is missing is the return format and any category-coverage caveat, which an agent needs to use the result correctly.

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% and the single parameter already enumerates example categories (pizza, burger, biryani, pasta, rice). The description adds nothing beyond 'by category', so the baseline 3 applies.

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?

States a specific verb and resource: 'Get a random food image by category from Foodish API.' It is distinguishable from foodish_random (which lacks the category filter) only by inference from the name, since the description never names that sibling.

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?

No guidance on when to use this versus foodish_random or the meal_* image/filter tools. The agent must infer that this is the category-scoped variant of foodish_random from the tool names alone.

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