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

With no annotations provided, the description carries the full burden of disclosing behavior. It clearly states the tool returns complete recipe details, that nutrition is computed from ingredient food rows rather than hand-entered, and that each figure traces back to national datasets cited by lookup_food. This adds meaningful transparency about data provenance and the no-cook constraint, going beyond just describing inputs and outputs. Minor gap: it doesn't explicitly state whether the tool creates, modifies, or has side effects, but the read-only nature is strongly implied.

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 compact and front-loaded: the first sentence delivers the core purpose and components, the second adds nutritional data provenance, and the third clarifies input format and the search alternative. Every sentence earns its place without redundant repetition of the tool title or input schema. It is informative yet 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 the tool has only one parameter, full schema coverage, and no output schema, the description provides all necessary context for correct invocation: what the tool returns, how to specify the recipe, and how to find one if only a name fragment is known. The context about data provenance and raw/vegan constraints is sufficient for an agent to decide when and how to use this tool. No missing critical information is evident.

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 description coverage is 100%, so the schema already documents the single parameter ('recipe') with an example value. The description adds extra meaning by explaining that the parameter accepts a slug OR a recipe name, and gives a concrete example format. This goes beyond the schema's basic 'Recipe slug or name' explanation, reinforcing the valid input format for correct invocation.

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 a specific verb ('Get'), a specific resource ('one Heathy recipe in full'), and enumerates exactly what is included: ingredients with food slugs and gram weights, method, per-serving nutrition, allergens, and carbon footprint. It also distinguishes itself from siblings by noting that search_recipes is used to find recipes. This is clearly differentiated from other tools like search_recipes, lookup_food, and food/nutrient lookup tools.

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: when you need a full recipe by slug or name, and it explicitly mentions using search_recipes to find one. It clarifies that all recipes are raw/no-cook and vegan, which helps an agent decide if this tool is appropriate given user constraints. It also implies the alternative path (search_recipes) without needing inference.

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