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enderekici

Trading 212 MCP Server

by enderekici

place_stop_limit_order

Execute a stop-limit order that converts to a limit order when a specified stop price is reached, allowing precise control over trade entry or exit points.

Instructions

Place a stop-limit order that becomes a limit order when the stop price is reached

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesThe ticker symbol of the instrument
quantityYesThe quantity to buy (positive) or sell (negative)
stopPriceYesThe stop price that triggers the limit order
limitPriceYesThe limit price for the order once triggered
timeValidityNoTime validity of the orderDAY

Implementation Reference

  • The implementation of the place_stop_limit_order tool, which calls the Trading 212 API endpoint /equity/orders/stop_limit.
    async placeStopLimitOrder(order: StopLimitOrderRequest): Promise<Order> {
      return this.request(
        '/equity/orders/stop_limit',
        {
          method: 'POST',
          body: JSON.stringify(order),
        },
        OrderSchema,
      );
    }
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. It mentions the order's triggering mechanism but fails to cover critical aspects like authentication requirements, rate limits, order confirmation, execution risks, or what happens on partial fills. For a financial trading tool with mutation implications, this is a significant gap.

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?

The description is a single, efficient sentence that front-loads the core functionality with zero wasted words. It directly communicates the tool's purpose 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?

For a complex financial order placement tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits (e.g., idempotency, error handling), return values, and practical usage constraints, leaving the agent under-informed for safe invocation.

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

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional semantic context about parameters beyond implying the relationship between stopPrice and limitPrice in the order logic, which is minimal value over the schema.

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

Purpose5/5

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

The description clearly states the specific action ('Place a stop-limit order') and explains the mechanism ('becomes a limit order when the stop price is reached'), distinguishing it from sibling tools like place_limit_order and place_stop_order by specifying the hybrid nature of this order type.

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?

The description provides no guidance on when to use this tool versus alternatives like place_limit_order or place_stop_order, nor does it mention prerequisites such as account authorization or market conditions. It merely states what the tool does without contextual usage advice.

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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