Bottles in the same style with a similar flavor profile at a lower price than the given bottle. Great for 'what tastes like X without the price tag' questions.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 5) | |
| bottle_id | Yes | Bottle UUID or name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is established. The description adds result-scoping detail (same style, similar flavor, lower price), but does not disclose ordering, output shape, or behavior when no cheaper alternative exists.
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?
Two short sentences carry all the needed information with no fluff. The main outcome is front-loaded, and the second sentence provides a useful real-world usage example.
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 read-only lookup tool with fully documented parameters and safety annotations, the description is largely complete. The main gap is the absence of any mention of return structure or behavior when no matches are found, but this is not critical for correct invocation.
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 coverage is 100%, so bottle_id and limit are already documented adequately. The description adds minimal semantic value by implying bottle_id is 'the given bottle,' but it does not enrich the meaning of the parameters beyond the schema.
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 defines the resource and criteria: bottles sharing style and flavor profile at a lower price than a given bottle. The 'lower price' qualifier helps distinguish it from siblings like find_similar, though it does not explicitly name alternatives.
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 gives a concrete usage context: 'what tastes like X without the price tag' questions. This clearly implies when the tool is appropriate, but it does not state when not to use it or mention sibling alternatives.
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 distinct purposes: search, get details, compare, find similar, find cheaper, recommend, suggest for tonight, and trending. However, 'find_similar' and 'find_cheaper_alternative' overlap somewhat in that both return similar bottles, though one explicitly filters by price. 'pour_tonight_suggestion' and 'get_recommendations' also both provide recommendations, but differ in input (mood/occasion vs. taste/budget).
Tool names follow a consistent verb_noun pattern: compare_bottles, find_cheaper_alternative, find_similar, get_bottle, get_recommendations, pour_tonight_suggestion, search_bottles, trending_bottles. The only minor deviation is 'pour_tonight_suggestion' which is a bit more descriptive than the others, but it still fits the pattern.
8 tools is well within the ideal 3-15 range. Each tool covers a distinct user need: searching, retrieving details, comparing, finding alternatives, getting recommendations, and seeing trends. No tool feels redundant or unnecessary.
The tool surface covers the core discovery and recommendation workflows well: search, get details, compare, find similar/cheaper, get personalized recommendations, and see trends. Minor gaps include no explicit tool for filtering by age or rating, and no way to get a list of all bottles in a category, but these are workable via search_bottles.