Openworker E-Commerce MCP Server

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ecommerce_match_variants

Matches product variants across e-commerce platforms using fuzzy logic. Maps candidate variants to a target to resolve mismatches and enable accurate product synchronization.

Instructions

Fuzzy match product variants across platforms

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "action": "<action>",
      "sourceName": "<sourceName>"
    },
    "name": "ecommerce_match_variants"
  }
}

Input Schema

Name	Required	Description	Default
`action`	Yes
`candidates`	No
`sourceName`	Yes
`targetCandidate`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 1, 2026

TDQS

C2.3/5.0

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only reveals that matching is 'fuzzy' or approximate; it does not explain whether 'force_map' writes permanent mappings, whether data is modified, or what the tool returns.

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?

The description is extremely concise with no filler, but it is under-specified rather than usefully concise. It reads more like a title than a functional description and lacks any structural separation of key operational details.

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

Completeness1/5

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

Given four parameters, no annotations, no output schema, and nested object parameters, the one-sentence description is insufficient. An agent cannot safely determine how to invoke the tool, what 'force_map' does, or what the outcome of the operation will be.

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

Parameters1/5

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

Schema description coverage is 0%, and the description adds no meaning for any of the four parameters. The distinction between 'match' and 'force_map', the role of 'sourceName', and the relationship between 'candidates' and 'targetCandidate' are left entirely to inference.

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 description names a specific verb ('Fuzzy match') and resource ('product variants across platforms'), making the core purpose immediately understandable. It is concise and distinct from most siblings, though it does not explicitly contrast with closely related tools like ecommerce_sync_multiplatform_stock.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention any preconditions, typical scenarios, or cases where another sibling would be better suited.

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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