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armorwallet
by armorwallet

get_all_orders

Retrieve a list of limit, take profit, and stop loss orders from the Armor Crypto MCP server. Filter results by status and specify the number of orders to return for efficient order management.

Instructions

Retrieve all limit, take profit and stop loss orders.

Returns a list of orders.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
get_all_orders_requestsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_order_responsesYes

Implementation Reference

  • The main handler function for the 'get_all_orders' tool. It is registered via the @mcp.tool() decorator, performs authentication check, and delegates to armor_client.list_orders().
    @mcp.tool()
    async def get_all_orders(get_all_orders_requests: ListOrderRequest) -> ListOrderResponseContainer:
        """
        Retrieve all limit, take profit and stop loss orders.
        
        Returns a list of orders.
        """
        if not armor_client:
            return [{"error": "Not logged in"}]
        try:
            result: ListOrderResponseContainer = await armor_client.list_orders(get_all_orders_requests)
            return result
        except Exception as e:
            return [{"error": str(e)}]
  • Pydantic schema for the input parameter ListOrderRequest used by the get_all_orders tool.
    class ListOrderRequest(BaseModel):
        status: Optional[Literal["OPEN", "CANCELLED", "EXPIRED", "COMPLETED", "FAILED", "IN_PROCESS"]] = Field(description="status of the orders, if specified filters results.")
        limit: Optional[int] = Field(default=30, description="number of most recent results to return")
  • Pydantic schema for OrderResponse, the core element in the tool's output.
    class OrderResponse(BaseModel):
        id: str = Field(description="unique identifier of the order")
        amount: float = Field(description="amount of tokens to invest")
        status: str = Field(description="current status of the order")
        input_token_data: TokenData = Field(description="details of the input token")
        output_token_data: TokenData = Field(description="details of the output token")
        wallet_name: str = Field(description="name of the wallet")
        execution_type: Literal["LIMIT", "STOP_LOSS", "TAKE_PROFIT"] = Field(description="type of the order")
        expiry_time: str = Field(description="expiry time of the order in ISO format")
        watchers: List[OrderWatcher] = Field(description="list of watchers for the order")
        transaction: Optional[dict] = Field(description="transaction details if any", default=None)
        created: str = Field(description="ISO 8601 timestamp of the creation of the order")
  • Pydantic schema for the output ListOrderResponseContainer wrapping list of OrderResponse.
    class ListOrderResponseContainer(BaseModel):
        list_order_responses: List[OrderResponse]
  • Helper method in ArmorWalletAPIClient that performs the API call to list orders, invoked by the tool handler.
    async def list_orders(self, data: ListOrderRequest) -> ListOrderResponseContainer:
        """List all orders."""
        payload = data.model_dump(exclude_none=True)
        return await self._api_call("POST", f"transactions/order/", payload)
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions the return type ('list of orders') but doesn't disclose pagination behavior, rate limits, authentication needs, or whether this is a read-only operation. For a tool that retrieves data, this leaves significant gaps in understanding its behavior.

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

Conciseness4/5

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

The description is appropriately brief with two sentences that directly state the purpose and return value. While minimal, it avoids redundancy and gets straight to the point without unnecessary elaboration.

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 tool has an output schema (which handles return values), the description's main gaps are in parameter explanation and behavioral context. With no annotations and poor parameter coverage, the description doesn't provide enough context for effective tool use, especially compared to sibling order-related tools.

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?

The description provides zero information about parameters, while the schema has 0% description coverage. The single parameter 'get_all_orders_requests' with its nested 'limit' and 'status' fields is completely undocumented in the description, failing to compensate for the schema's lack of parameter explanations.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'retrieves all limit, take profit and stop loss orders' which clarifies the verb (retrieve) and resource (specific order types). However, it doesn't differentiate from sibling tools like 'list_dca_orders' or 'cancel_order', leaving ambiguity about when to use this versus other order-related tools.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context for usage, or comparisons to sibling tools like 'list_dca_orders' or 'cancel_order', leaving the agent without clear selection criteria.

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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