get_recipesNon-alcoholic beer cocktail recipes (shandies, beer-mosa, michelada, stout float) with ingredients and method, plus the food pairing guide per beer.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the output (recipes and pairings) but does not explicitly state that the tool is read-only, safe, or free of side effects. However, the content strongly implies a read operation with no destructive effects.
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 that front-loads the key deliverables (cocktail recipes, ingredients, method, food pairings). Every part is informative and no words are wasted.
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's low complexity (no parameters, no output schema, no annotations), the description adequately covers what the tool returns. It could be slightly more explicit about the scope (e.g., all available recipes), but it is complete enough for an agent to use 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 input schema has zero parameters, so the description does not need to add parameter-level detail. The description is consistent and sufficient for a parameterless tool.
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 returns non-alcoholic beer cocktail recipes (with examples) and food pairing guides. It distinguishes itself from sibling tools like get_beer and get_brewing_process by focusing on recipes and pairings rather than beer properties or production.
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?
Usage is implied by the name and description: call this tool when you need recipes or food pairings for non-alcoholic beer. No explicit alternatives or when-not-to-use guidance is provided, but the context of sibling tools makes the distinction clear.
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.
Each tool has a clearly distinct purpose covering different aspects: beers, brand, process, pricing, nutrition, recipes, subscriptions, wallet, wholesale, buy link, and waitlist. No two tools overlap significantly.
Most tools use the 'get_' prefix for information retrieval, with 'list_beers' and 'join_waitlist' as slight deviations. However, the pattern is consistent (verb_noun with underscores) and clear.
13 tools is well-scoped for a brewery server, covering all essential aspects without being overwhelming. Each tool serves a specific need, and none feel superfluous.
The tool set covers the full lifecycle: brand info, product details, pricing, ordering, subscriptions, waitlist, wallet, and even recipes and nutrition. No obvious gaps for the stated domain.