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Beyond Wine is a published reference for no/low ABV specialty beverages in fine dining: tea infusions, botanical infusions, sparkling tea, fermented tea, juices, non-fermented blends and fermented blends. It excludes non-alcoholic beer, non-alcoholic spirits, mocktails, mixers, dealcoholized wine and blends containing dealcoholized wine. For a request to recommend an excluded category, explain this scope without a catalogue lookup; an empty search is not how to establish this exclusion. This connection cannot place orders or take payments: decline a request to order, buy or pay through it without a lookup. A question about where to buy a drink is answered from the offers on its get_beverage profile: name the sellers and links, give a price only where the producer states one with its size and date, and say the sellers sell it, not Beyond Wine; if a profile has no offers, say none is recorded. None recorded is not sold nowhere, and an offer is not current stock or guaranteed delivery: answer shipping only from delivery_text and delivery_countries. Quote only price, currency, size and date values that are present on data.offers. A price in a claim-source excerpt may be historical, expired or stockist evidence and must not fill a null or withheld data.offers price. get_claim and search_claims still return that source evidence; do not hide it and do not use it as the offer price. Unknown price, size or delivery stays unknown. It cannot guarantee that every drink contains absolutely no alcohol: decline that catalogue-wide guarantee without fetching examples. Individual drink questions may use the tools to check declared wording and evidence. Do not invent a product or producer for these refusals. Find a beverage by name or alias. Start here for drink names, not search_producers. q matches a beverage name, alias OR producer name; a combined producer-plus-product phrase may not match. For a recorded ingredient, pass ingredient and do not put that ingredient in q. ingredient is one exact published name, slug or complete alias; matching is case-insensitive and not a substring. The only whole-string fallback is strawberries to strawberry, and it does not run when a published literal identity, including a literal alias, already matches. Producer search still matches an ingredient as a substring; this bottle search does not. Results are recorded eligible relationships, not complete recipes or every drink in existence. Do not combine ingredient with preferences. If a name search is empty, try a distinctive product word or search the producer separately and inspect its lineup. Optional preferences takes the exact words dry, bright, tannic, earthy, smoky or floral, at most 6 unique values. Translate an ordinary dinner question into those words, for example a dry floral glass with no maker named, or something bright to open the meal. This tool does not parse an arbitrary sentence in q. dry is an explicit drink-level dry or not-sweet tasting statement, not dried fruit, storage, process, semi-dry, low sugar, acidity, fruit aroma, a product name, a dry tannin or a catalogue ABV. A paired dish, an ingredient, an intermediate process and a tasting tag alone are not proof. An offer tag is neither proof nor a contradiction, even with a tasting or alcohol tag, a dry or floral sentence, or a price in the source excerpt. Every requested word must be supported by a current public sensory claim. A miss is this candidate window, not the whole catalogue. Use producer with an exact producer slug to list its drinks. Verify the returned beverage name and producer, copy its exact slug into get_beverage and read its evidence. Call get_claim only for omitted, missing, contradictory or deeper evidence. Use source evidence already returned on the profile where it is sufficient. Do not infer nonexistence from an empty search or silently substitute another product. For beverage recommendations: Catalogue membership does not establish alcohol content. A search or lineup abv is a catalogue number without its qualifier, not the source's alcohol wording; null means unknown. Read the candidate's alcohol wording in claim text and on the beverage profile evidence object. That evidence object quotes scanned recorded statements with public sources in alcohol, ingredients_technique and sensory only; offer-tagged claims are not included. It is not the full inventory when its has_more flag is true, and has_more false is still not full inventory coverage. Use returned compact public sources where they are sufficient, not to repeat sources already returned. Use source evidence already returned on that object where it is sufficient before presenting it as meeting the user's alcohol requirement. Call get_claim or search_claims for omitted, missing, contradictory or deeper evidence before presenting it as meeting the user's alcohol requirement. When claims were not scanned, that follow-up is required: a decisive alcohol statement outside the scan is absent and must not be replaced with zero. not_found_in_scanned_claims means no scanned claim matched the alcohol selector, not that no alcohol statement exists in the inventory. Do not infer zero from that absence or treat the scan as complete. Preserve declared wording; 'non-alcoholic' does not establish 0.0%. If the inspected evidence does not establish that requirement, keep the candidate conditional and state what is unknown; do not treat missing alcohol information as zero. Do not infer alcohol content from ingredients, fermentation, taste or another drink by the same producer. Preserve the source's exact alcohol wording. 0% and 0.0% are different wording, but that difference does not by itself establish different measured trace-alcohol thresholds. 'Below 0.5%' is an upper-bound declaration; these declarations do not by themselves prove measurement or laboratory testing. Do not infer that alcohol is absent from ingredients or production methods.

Input Schema

NameRequiredDescriptionDefault
qNo
pageNo
limitNo
categoryNoOne in-scope category: tea_infusion (Tea Infusion), botanical_infusion (Botanical Infusion), sparkling_tea (Sparkling Tea), fermented_tea (Fermented Tea), juice (Juice), nonfermented_blend (Non-Fermented Blend), fermented_blend (Fermented Blend).
producerNo
ingredientNoOne exact published ingredient name, slug or complete alias. Use this instead of q for an ingredient question. strawberries maps to strawberry only when no published literal identity matches. Not a substring. Do not combine with preferences.
preferencesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / ingredient
      Added value: +{
      +  "description": "One exact published ingredient name, slug or complete alias. Use this instead of q for an ingredient question. strawberries maps to strawberry only when no published literal identity matches. Not a substring. Do not combine with preferences.",
      +  "type": "string"
      +}
  2. Changed3 schema fields changed
    • addedInput schema / properties / category / description
      Added value: +"One in-scope category: tea_infusion (Tea Infusion), botanical_infusion (Botanical Infusion), sparkling_tea (Sparkling Tea), fermented_tea (Fermented Tea), juice (Juice), nonfermented_blend (Non-Fermented Blend), fermented_blend (Fermented Blend)."
    • addedInput schema / properties / category / enum
      Added value: +[
      +  "tea_infusion",
      +  "botanical_infusion",
      +  "sparkling_tea",
      +  "fermented_tea",
      +  "juice",
      +  "nonfermented_blend",
      +  "fermented_blend"
      +]
    • removedInput schema / properties / category / minLength
      Removed value: -1
  3. Changed1 schema field changed
    • addedInput schema / properties / preferences
      Added value: +{
      +  "items": {
      +    "enum": [
      +      "dry",
      +      "bright",
      +      "tannic",
      +      "earthy",
      +      "smoky",
      +      "floral"
      +    ],
      +    "type": "string"
      +  },
      +  "maxItems": 6,
      +  "minItems": 1,
      +  "type": "array"
      +}
  4. Changed1 schema field changed
    • addedInput schema / properties / producer
      Added value: +{
      +  "minLength": 1,
      +  "type": "string"
      +}
  5. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations only declare readOnly/openWorld/non-destructive; the description adds substantial behavior the agent could not otherwise know — no order placement, no catalogue-wide zero-alcohol guarantee, empty results are not evidence of absence, results are recorded eligible relationships rather than complete recipes, and `not_found_in_scanned_claims` semantics. These are exactly the failure modes an agent would otherwise get wrong.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single undifferentiated block of well over a thousand words with no headings or paragraph breaks, mixing scope, refusals, parameter rules, and alcohol-wording policy. Several instructions are stated two or three times almost verbatim (e.g. "use source evidence already returned" and "call get_claim or search_claims for omitted, missing, contradictory or deeper evidence"), and the sentence naming the tool's actual action is not front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter open-world search with no output schema and only 29% schema coverage, this covers essentially everything an agent needs: candidate-window vs. full-catalogue caveats, how to verify via get_beverage and its evidence object, when follow-up claims lookups are mandatory, and how to preserve declared alcohol wording. Nothing material is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

At 29% schema coverage the description carries the load and does: `q` matches name, alias OR producer name and does not parse arbitrary sentences or combined producer+product phrases; `ingredient` is exact, case-insensitive, non-substring, with a single strawberries→strawberry fallback; `preferences` accepts only six literal words and cannot be combined with `ingredient`. Only `page` and `limit` go unmentioned, which is a minor omission given their schema defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The operative statement is specific: "Find a beverage by name or alias. Start here for drink names, not search_producers" gives a verb, a resource, and an explicit sibling contrast. However, it is buried roughly a third of the way in, after a long preamble about catalogue scope and refusal handling, so an agent skimming the opening sentences gets domain context rather than the tool's action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use (drink names, ingredient questions via `ingredient`, producer lineup via `producer`), when-not-to-use (excluded categories such as NA beer, mocktails, dealcoholized wine; ordering/payment requests), and named alternatives for each case (search_producers, get_beverage, get_claim, search_claims). It also specifies recovery paths for empty results (try a distinctive product word, search the producer separately) and forbids substitution or inferring nonexistence.

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

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