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search_products

Semantic search over the location's catalog: product/dish names, descriptions, specifications, brand, SKU/barcodes and attached docs. Use for "do you have…" / "recommend…" / "how much is…" questions instead of paging through get_menu. Returns matching items with prices and a relevance score; falls back with a note when the search index is unavailable for the location.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many items to return (1–10, default 6)
queryYesWhat the guest is looking for, in any language
domainYes
languageNoISO 639-1 menu language, default en

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description discloses meaningful behavior: it returns 'matching items with prices and a relevance score', notes fallback when the search index is unavailable, and indicates semantic (fuzzy) matching. It stops short of describing ordering details or permission requirements, but for a read-only search this is well above average.

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

Conciseness5/5

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

Two sentences, no filler. The first sentence states purpose and scope, the second gives usage scenarios and return/fallback behavior. Every part earns its place.

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

Completeness4/5

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

No output schema or annotations exist, but the description covers what is searched, when to use it, what it returns, and a fallback scenario. It doesn't detail the item structure or error handling beyond the fallback, but for a search tool with four simple parameters this is sufficient for an agent to select and invoke it correctly.

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

Parameters3/5

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

The schema already covers three of four parameters (query, limit, language) with descriptions; the missing 'domain' parameter is hinted at by 'location's catalog' but not explicitly explained. Since schema coverage is 75% (just below the 80% baseline), the description adds little beyond the schema. It provides no new details on limit or language.

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

Purpose5/5

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

The description opens with 'Semantic search over the location's catalog' – a specific verb and resource. It enumerates searchable fields (names, descriptions, specifications, brand, SKU/barcodes, docs) which clearly distinguishes it from siblings like get_menu. The explicit 'instead of paging through get_menu' further differentiates it.

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?

The description provides explicit when-to-use examples ('do you have…' / 'recommend…' / 'how much is…') and names the alternative tool to avoid (get_menu). The fallback note also sets expectations for degraded mode, which is a clear usage signal.

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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TDQS

A3.8/5.0
Disambiguation5/5

Each tool targets a distinct resource/action: menu, item, search, cart, order, reservation, availability, store info, and policies. Even similar tools like get_item vs search_products are clearly differentiated by exact lookup vs semantic search. There is no meaningful overlap.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (get_, create_, cancel_, check_, update_, search_). No mixed conventions or stylistic deviations exist.

Tool Count5/5

13 tools is well-scoped for the guest-facing restaurant domain, covering menu browsing, search, cart, orders, reservations, store info, and policies. Each tool is justified and the count is within the ideal range.

Completeness4/5

Core lifecycle coverage is solid: menu, cart, order placement/status, reservations, and availability are all covered. The only notable gap is the absence of an order cancellation tool, but this may be intentional and does not block primary workflows.

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