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

Annotations already declare the tool read-only and idempotent, and the description adds meaningful behavioral details beyond that: every query word must appear in one recipe, multiple ingredient terms can cause empty results rather than a coverage report, and the return is a shortlist with title, URL, description, time, servings, and categories. It also explains the rationale that results are real pages, not remembered guesses.

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 primary use case and remains information-dense despite its length. Each sentence contributes useful practical context, such as when to use the tool, how it differs from the sibling, and what its result payload looks like. There is no filler or repetition pulling away from the essential content.

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?

With no output schema present, the description compensates by listing exactly what the shortlist returns, including title, URL, description, total time, servings, and categories. The schema complements pagination and parameter details, while the description gives the matching behavior and the rationale for using the tool rather than guessing. It feels complete enough for selection and invocation.

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?

Since the input schema covers 100% of the parameters, the baseline is a 3, but the description adds valuable insight beyond the schema. It explains that every query word must appear in a single recipe, that ingredient-packed searches will have no results, and that omitting the parameter lists every recipe newest-first—details that make invocation predictable.

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 opens with a concrete action, 'Find something to cook,' and clearly identifies the resource as recipes published at recipes-daily.com. It also distinguishes this tool from its sibling, find_recipes_by_ingredients, by explaining the input-matching difference, so an agent can immediately tell them apart.

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 says to call this tool for any question about what to make, including dish names, cuisines, time budgets, or a week of dinners. It then directs users to the sibling for ingredient-based requests and even explains the failure mode of using this tool that way. This provides both clear when-to-use and clear when-not-to-use guidance.

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