list_beersFull product lineup with style, tasting profile, ABV, calories, carbs, pricing (can/6-pack in INR), food pairings, availability status, and brewing notes.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, but the description thoroughly lists the data fields returned. However, it lacks explicit behavioral traits such as read-only nature or any ordering, which would add transparency.
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, efficient sentence that packs in all relevant details without wordiness. It is front-loaded with purpose and enumeration.
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 no output schema, the description provides a comprehensive list of returned data fields, covering style, profile, ABV, pricing, etc. It is complete for a no-parameter list tool.
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?
With zero parameters, the baseline is 4. The description adds no parameter information, but there are no parameters to describe, so this score 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 it lists the 'full product lineup' and enumerates specific attributes (style, tasting profile, ABV, etc.). It distinguishes from siblings like get_beer by emphasizing it's the complete lineup.
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 implies use for a broad overview rather than individual beer details, but does not explicitly state when to use versus alternatives or include any when-not guidance.
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.