Check the status and delivered content of one of your orders by order_code (requires your api_key). Kiểm tra trạng thái & nội dung đã giao của 1 đơn theo order_code (cần api_key).
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes | Your shop account API key. | |
| order_code | Yes | The order code returned by buy_product. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of explaining behavior. It clearly indicates this is a read-style lookup ('check'), states what is returned ('status and delivered content'), and calls out the authentication requirement ('requires your api_key'). It does not mention possible error cases or output format, but for a simple status lookup this is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the main action. The bilingual duplication is mildly redundant for an AI agent, but it is compact and each version adds clarity for the intended audience.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter, no-nested-object lookup tool, the description plus schema covers the essential invocation details. It lacks explicit mention of the expected response shape and does not directly tie order_code to the buy_product sibling, but these are minor gaps for this tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already documents both api_key and order_code. The description adds little beyond restating that api_key is required and that lookup is by order_code, so it does not meaningfully exceed the schema's baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('check'), a specific resource ('one of your orders'), and the scope ('status and delivered content by order_code'). This clearly distinguishes it from siblings like buy_product or quote_order, which handle ordering rather than checking an existing order.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after an order exists: it checks 'one of your orders' using an order_code and requires an api_key. However, it does not explicitly say when to use this tool instead of alternatives or exclude cases, such as checking multiple orders or checking before an order is confirmed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Product discovery tools such as best_sellers, latest_products, recommend_products, and similar_products have related listing purposes and could be confused, though descriptions clarify sorting and filtering criteria. Social-check tools also overlap: check_live_facebook, deep_inspect, and check_health_bulk can all verify Facebook accounts. Most tools are distinct, but the boundaries are not always crisp.
The dominant convention is snake_case verb_noun, e.g. buy_product, search_products, list_categories, check_order_status. A few names deviate, such as best_sellers, latest_products, similar_products, how_to_start, and deep_inspect, but they are still readable and predictable.
With 19 tools, the set falls into the 16-25 heavy range and could be trimmed: there are nine product-listing/search/recommend tools and three overlapping social-check tools. The count is not extreme, and the combined commerce-plus-verification scope is covered, but it feels heavier than necessary.
The core commerce workflow is complete: discover products, quote, confirm purchase, check order status, and view balance. Minor gaps include no order-history tool, no cancellation tool, and no actual top-up execution, but these are workaroundable for the stated shop purpose.