List all available cuisines on SAVOR Dish with recipe counts. Discover world cuisines and how many recipes are available for each. TRIGGERS:
'what cuisines do you have', 'list all cuisines'
'available food categories', 'cuisine options'
'how many recipes do you have', 'recipe categories'
| Name | Required | Description | Default |
|---|---|---|---|
| minRecipes | No | Only show cuisines with at least this many recipes (default 1) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, providing the core safety profile. The description adds output context ('with recipe counts') but does not disclose additional behavioral traits beyond what annotations already cover.
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 two sentences plus a trigger list. The first sentence is clear and direct, while the second sentence somewhat restates the first. The trigger list is helpful but adds length. Overall, it is reasonably concise.
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 list tool with one optional parameter and comprehensive annotations, the description is complete. It explains what data is returned (cuisines with recipe counts) and provides example user queries, giving the agent sufficient context to invoke it correctly.
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?
The single parameter minRecipes is fully documented in the schema with a description, default, minimum, and maximum. The description adds no additional parameter semantics, and with 100% schema coverage, the baseline score 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 clearly states 'List all available cuisines on SAVOR Dish with recipe counts', which is a specific verb+resource combination. It also distinguishes this tool from sibling tools like recipes_list_by_cuisine by focusing on cuisine categories rather than individual recipes.
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 explicit example queries that indicate when to use this tool, such as 'what cuisines do you have' and 'list all cuisines'. This gives clear context, though it does not explicitly mention alternatives or when not to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes across cooking, nutrition, recipes, and shopping domains, with minimal overlap. However, some potential confusion exists between 'nutrition_analyze' and 'recipes_get_nutrition' (both provide nutritional analysis) and between 'recipes_find_by_ingredient' and 'recipes_search' (both handle ingredient-based filtering). Descriptions help differentiate, but the boundaries could be clearer.
Tool names follow a highly consistent snake_case pattern with clear domain prefixes (cooking_, nutrition_, recipes_, etc.) and descriptive action_noun combinations. Examples like 'cooking_convert_units', 'nutrition_analyze', and 'recipes_get_dietary' demonstrate uniform conventions throughout the set, making them predictable and readable.
With 31 tools, the count feels excessive for a cooking/recipe server, leading to potential cognitive overload and redundancy. While the domain is broad, many tools could be consolidated (e.g., multiple nutrition tools or recipe filters) without losing functionality. A more streamlined set of 15-20 tools would better serve the scope.
The tool set comprehensively covers the cooking and recipe domain, including CRUD-like operations (e.g., get, search, compare), nutritional analysis, meal planning, shopping integration, and platform info. There are no obvious gaps; tools support full workflows from discovery to preparation, with dietary, seasonal, and practical considerations addressed.
