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

Annotations already provide readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds that results include nutrition data, but does not disclose other behavioral traits (e.g., pagination, rate limits). No contradiction with annotations, but minimal extra value beyond them.

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 a single sentence with 24 words, front-loading the core purpose. Every word conveys meaningful information without redundancy. Highly efficient and easy to parse.

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 complexity of 8 optional parameters and existence of an output schema, the description covers key features like filters and included nutrition data. However, it lacks guidance on selecting this tool over sibling tools. Still, it provides sufficient context for typical recipe search tasks.

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 has 100% coverage for all 8 parameters. The description adds value by mentioning specific dietary filters (vegan, keto, gluten-free) and noting that results include nutrition data, which supplements the schema. This justifies a score above baseline 3.

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 searches over 365K recipes with various filters (dietary, cuisine, meal type, max prep time) and mentions nutrition data. It effectively distinguishes from siblings like analyze, by_ingredients, and details by focusing on search and filtering.

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 does not explicitly state when to use this tool versus alternatives. It lists available filters but lacks contrast with sibling tools like spoonacular.recipes.analyze or spoonacular.recipes.by_ingredients. Usage context is implied but not clearly guided.

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