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tukimtk-design

Openworker E-Commerce MCP Server

ecommerce_get_store_metrics

Get store metrics to identify pending shipment orders and low-stock SKUs across Shopee, TikTok Shop, and Lazada.

Instructions

ดึงข้อมูลสรุปออเดอร์ค้างจัดส่งและรายการ SKU ที่สต็อกกำลังหมด

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
platformYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are present, so the description carries the full burden. The verb "ดึงข้อมูล" (retrieve) implies a read-only operation and the description states what data is returned, but it does not mention whether results are live/cached, whether a session or auth is required, or any rate-limit side effects. For a simple getter this is minimally adequate but not rich.

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?

A single sentence with no filler; the verb and main output concepts are front-loaded. Every word earns its place, and there is no redundant repetition of the tool name or title.

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

Completeness3/5

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

For a one-parameter read-only metrics tool, the description states the main purpose and returned data categories, and the schema covers the platform constraint. However, with no output schema, no annotations, and no usage guidance, the overall context is only minimally sufficient for an agent to confidently select and invoke the tool.

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 never mentions the platform parameter or how the chosen platform affects the output. The enum values are self-explanatory, but the description does not compensate for the low schema coverage as required.

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 uses a specific verb ("ดึงข้อมูล" / retrieve) and names concrete resources: a summary of pending-delivery orders and low-stock SKUs. This makes it meaningfully distinct from generic store-metric naming and from the sibling ecommerce_get_pending_orders, though it does not explicitly name that sibling.

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 about when to choose this tool over ecommerce_get_pending_orders, ecommerce_product_search, or the other metric/stock-related siblings. No prerequisites, exclusions, or preferred contexts are provided; usage is only weakly implied by the name and description.

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