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tukimtk-design

Openworker E-Commerce MCP Server

ecommerce_auto_reply_chat

Manage e-commerce customer chats by fetching unread messages and sending automated replies across Shopee, TikTok Shop, and Lazada.

Instructions

Fetch unread messages and auto-reply

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYes
platformYes
messageIdNo
replyTextNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it only states the two actions. It does not say whether auto-replying actually sends messages, marks them as read, overwrites existing replies, or requires special permissions. This is a meaningful transparency gap for a tool that sends responses on behalf of the user.

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

Conciseness3/5

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

The description is short and contains no filler, but it reads more like a tagline than a structured tool specification. It front-loads the two operations, yet it is too terse to convey the operational detail needed for a 4-parameter tool.

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

Completeness2/5

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

Given the 0% schema coverage, missing annotations, and no output schema, the description is not sufficient for an agent to invoke the tool correctly. It omits platform specifics, conditional parameter requirements, and behavioral side effects, leaving several important decisions to inference.

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

Parameters2/5

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 parameter-level meaning. The action enum is self-explanatory, but the required `platform` parameter's allowed values are unknown, and the conditional relationship of `messageId` and `replyText` to the `reply` action is not described. The description fails to compensate for the absent schema descriptions.

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 clear operation pair — fetching unread messages and auto-replying — which maps directly to the action enum. It is specific enough to identify the tool's chat-focused purpose and to distinguish it from the order/product/SEO siblings, though it doesn't explicitly mention the e-commerce chat scope.

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?

There is no guidance on when to use this tool versus alternatives, no exclusions, and no mention of prerequisites such as needing an active session or authenticated store. The only usage signal is the implicit one in the name and description, so an agent gets little help deciding between fetch_unread and reply beyond reading the schema.

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