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tiffany_suggest

Retrieve Tiffany & Co. search-box suggestions for partial queries, returning suggested phrases with live result counts to reveal search trends and catalog demand.

Instructions

Get Tiffany & Co. search-box suggestions. Returns Tiffany & Co.'s own search-box suggestions (typeahead) for a partial query -- a flat list of suggested search phrases, each with its own live total result count on the product catalog. Not product data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesPartial search query

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it delivers: it discloses the source (Tiffany & Co.'s own search box), the input shape (partial query), the output shape (flat list of suggested phrases), and the key behavior that each suggestion includes a live product-catalog result count. It also explicitly warns that the tool does not return product data.

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 efficient sentences with no filler. The core action and output structure are front-loaded, and the important caveat 'Not product data' is placed at the end without bloating the definition.

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 one-parameter, no-output-schema suggest tool, this description is complete. An agent knows what to pass, what to expect back, and what the data represents. No critical usage behavior is missing.

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 provides 100% coverage for the single 'query' parameter with 'Partial search query.' The description reinforces this by calling it a partial query and linking it to typeahead behavior, but it does not add materially new parameter-level information such as length limits, expected formats, or example values.

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 a specific verb and resource: 'Get Tiffany & Co. search-box suggestions.' It clarifies what kind of data is returned (typeahead suggestions with per-phrase result counts) and explicitly states 'Not product data,' which distinguishes it from sibling tools like tiffany_search and tiffany_product.

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

Usage Guidelines4/5

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

The description clearly communicates the intended use case: retrieving typeahead suggestions for a partial query. It also implies a when-not-to-use by stating the result is not product data, but it does not explicitly name an alternative tool such as tiffany_search for full product search.

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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