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darved2305

groww-mcp

by darved2305

cancel_order

Cancel pending orders on Groww by providing the order ID to manage equity holdings and trade execution.

Instructions

Cancel a pending order by order ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
order_idYesOrder ID to cancel

Implementation Reference

  • Handler implementation and registration for the cancel_order tool.
    // ── cancel_order ──────────────────────────────────────────
    server.tool(
      "cancel_order",
      "Cancel a pending order by order ID",
      {
        order_id: z.string().describe("Order ID to cancel"),
      },
      async ({ order_id }) => {
        try {
          const result = await growwClient.cancelOrder(order_id);
          const text = [
            `❌ ORDER CANCELLED`,
            `${"─".repeat(40)}`,
            `Order ID: ${result.orderId}`,
            `Status:   ${result.status}`,
            `${result.message}`,
          ].join("\n");
          return mcpText(text);
        } catch (err) {
          return mcpError(normalizeError(err));
        }
      }
    );
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Cancel') but lacks details on permissions required, whether cancellation is reversible, rate limits, or what happens if the order isn't pending. This leaves significant gaps for a mutation tool.

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 with zero wasted words. It's front-loaded with the core purpose and appropriately sized for the tool's complexity.

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 mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what happens after cancellation (e.g., confirmation message, error conditions), nor does it address behavioral aspects like permissions or side effects, leaving the agent with insufficient context.

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%, with the single parameter 'order_id' well-documented in the schema. The description adds no additional parameter semantics beyond what the schema already provides, meeting the baseline for high schema coverage.

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 clearly states the action ('Cancel') and target resource ('a pending order'), providing specific verb+resource pairing. However, it doesn't differentiate from sibling tools like 'modify_order' which might also handle order modifications, leaving room for ambiguity about when to choose one over the other.

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 'modify_order' or 'get_order_status'. It mentions 'pending order' but doesn't specify what qualifies as pending or whether it works on other order states, offering minimal contextual direction.

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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