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aliexpress_suggest

Retrieve AliExpress search-box keyword completions for a query and get a ready-to-use search URL for each suggestion.

Instructions

Suggest AliExpress search keywords. Returns AliExpress's own search-box keyword completions for a query, with a ready-to-use search URL for each suggestion. This is a suggestion/autocomplete surface, not a product feed: the upstream payload contains keyword strings only, so no product id, title, price or seller is returned. AliExpress usually offers 10-12 suggestions; each suggestion's url is the matching AliExpress search page and can be passed to the search endpoint as q.

Input Schema

NameRequiredDescriptionDefault
qYesPartial or full search keywords to complete
limitNoMaximum suggestions to return (1-20), defaults to 10

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.16

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the payload shape (keyword strings only, no product id/title/price/seller), typical result count (10-12), and the meaning of the url field. It stops short of mentioning rate limits, error behavior, or what an empty result means.

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?

Four short sentences, front-loaded with the verb and resource, then behavior, then scope exclusion, then return shape. No sentence is redundant given the absence of annotations and output schema.

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?

With no annotations and no output schema, the description must explain return values itself, which it does (keyword strings plus per-suggestion search URL, no product fields). The remaining gap is minor: the truncation behavior when limit exceeds the upstream 10-12 suggestions is not stated.

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?

Schema description coverage is 100%, so both q and limit are already documented upstream; baseline 3 applies. The description adds only a little semantic value over the schema, notably that q can be a partial or full query whose completion drives the search URL, but it never explains how the 10-12 default interacts with the limit parameter.

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?

States a specific verb+resource ("Suggest AliExpress search keywords") and immediately distinguishes the surface from a product feed: "This is a suggestion/autocomplete surface, not a product feed." It also pre-empts confusion with the sibling aliexpress_search by explaining that its output feeds that endpoint.

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?

Explains that this is an autocomplete surface and that each suggestion's url is the matching AliExpress search page which "can be passed to the search endpoint as q", giving a clear hand-off path to aliexpress_search. It does not compare against other keyword surfaces such as aliexpress_trending_searches, so the exclusion set is only partly covered.

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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