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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing the safety profile. The description adds value by describing the return behavior: it returns original ingredients with a multiplier, which is a meaningful behavioral detail beyond the annotations. 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 succinct and well-structured: a one-sentence purpose statement followed by a relevant trigger list. Every sentence serves a purpose, and the triggers are practical without being redundant. The format is easy to scan for an AI agent.

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 simple, two-parameter, read-only scaling tool, the description is complete. It covers the core function, return value shape, and typical user phrasings. No output schema exists, but the description gives a sufficient hint of the result without needing further detail. The combination of schema annotations and description fully equips an agent.

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: recipeSlug includes an example ('chicken-pho') and targetServings has a range (1-100). The description provides trigger examples but no additional parameter semantics beyond what the schema already documents, so a baseline of 3 is appropriate.

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 states the tool's purpose with a specific verb and resource: 'Scale a recipe for different serving sizes.' It also clarifies the output ('Returns the original ingredients with a scaling multiplier to adjust quantities'), which distinguishes it from sibling tools like recipes_get or recipes_search that fetch or search rather than scale.

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 TRIGGERS section provides concrete example phrases for when to use the tool, such as 'scale recipe X for 8 people' and 'halve the recipe'. This gives clear usage context without explicitly naming alternatives, but the scope is well-defined and distinct from sibling tools like cooking_convert_units or recipes_compare.

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