Retrieve orders by customer ID to inspect order data in fault-injection test scenarios. Returns order records for verification.
list_orders: list on orders
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "list_orders"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| customer_id | No |
Changes observed during successful MCP inspections.
v0.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits, but it only restates the action. It does not clarify read-only behavior, pagination, filtering, authorization, or return shape; the word 'list' weakly implies a fetch but no meaningful behavioral context is added.
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 text is short but under-specified rather than concise. The phrase 'list on orders' is ungrammatical, and no useful information is effectively front-loaded; a more informative one-liner would not be longer.
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 simple one-parameter list tool, the description at least indicates it retrieves orders, but it leaves out the meaning of the optional customer_id, how it differs from get_order, and what the response contains. With no annotations or output schema, this is insufficient for reliable tool selection and invocation.
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 description coverage is 0% and the description does not explain customer_id, whether it filters results, or what default null means. The parameter name offers some hint, but the description adds no semantic value beyond the schema.
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 'list_orders: list on orders' is essentially a restatement of the tool name and adds no definitional value. It says the tool lists orders, but does not specify scope (all orders, by customer, by date) or what distinguishes it from get_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?
There is no guidance about when to use list_orders versus siblings get_order, create_return, or issue_refund. It does not mention that get_order is likely for a single order or that create_return and issue_refund are for post-order operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.