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

There are no annotations, so the description carries the behavioral burden. It discloses that recipes are original, that nutrition figures derive from the same food rows lookup_food returns and are therefore checkable, and that results are ranked summaries rather than full recipes. It doesn't specify ranking order or pagination, but the key consumer expectations are stated.

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 core purpose and every sentence earns its place: search scope, data provenance, result granularity/next step, and alternative routing. It is dense but not bloated, and the most important operational information comes first.

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 read tool with 7 optional parameters, no annotations, and no output schema, the description is largely complete: it defines the object type, explains result granularity, points to get_recipe for details, and warns when health_topic is more appropriate. A small gap is that 'ranked summaries' doesn't convey exactly what fields appear or how ranking is determined, but this is not fatal given the follow-up pointer.

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 baseline is 3. The description enumerates the facets ('free text, health goal, category, ingredient, time or allergen') that map to query, goal, category, ingredient, max_time, and exclude_allergens, but it adds no constraints, formats, or meaning beyond what the schema already provides. The schema's examples are richer than the description on parameter usage.

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 uses a specific verb ('Find') and resource ('raw / no-cook vegan recipes'), and clearly identifies the search facets: free text, health goal, category, ingredient, time, and allergen. It also contrasts itself with get_recipe (summaries vs full details) and health_topic, making sibling differentiation explicit.

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?

It gives explicit routing guidance: for 'what should I eat for X' questions, prefer health_topic first; for full recipe details, call get_recipe with a slug. This is clear when-to-use and alternative guidance, not just implied context.

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