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kapruka_track_order

Read-only

Look up status and delivery progress for a Kapruka order by order number.

Returns current status (received / confirmed / out-for-delivery / delivered /
cancelled), the recipient and delivery details on file, a timestamped progress
timeline, the cart contents, and flags for whether a delivery photo or video is
available. Use this after a customer has placed and paid for an order and reads
back the order number from their confirmation email or the order complete page.

The order number is NOT the `order_ref` returned by kapruka_create_order
(which is the pre-payment checkout reference). Once the customer completes
payment in the browser, Kapruka emails them a separate order number — that
is what this tool expects.

Args:
    params (TrackOrderInput):
        - order_number (str): Kapruka order number (e.g. 'VIMP34456CB2')
        - response_format (str): 'markdown' (default) or 'json'

Returns:
    str: Order tracking details in the requested format.

    JSON schema:
    {
      "order_number": str,
      "pnref": str,                 # internal payment reference (numeric; not the same as order_number)
      "status": str,                # received | confirmed | shipped | delivered | cancelled | ...
      "status_display": str,        # human label
      "order_date": str,            # human-formatted, Asia/Colombo
      "delivery_date": str,         # human-formatted
      "shipped_date": str | null,
      "amount": str,                # LKR string (e.g. "15500.00")
      "payment_method": str,
      "comments": str | null,
      "recipient": {"name": str, "phone": str, "address": str, "city": str},
      "greeting_message": str | null,
      "special_instructions": str | null,
      "progress": [{"step": str, "timestamp": str}],
      "live_tracking_available": bool,
      "has_delivery_video": bool,
      "has_delivery_photo": bool,
      "items": [{"product_id": str, "name": str, "quantity": int, "selling_price": float}]
    }

    Error: "Error: <message>" on failure (e.g. order not found).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.7/5.0
Behavior5/5

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

The description goes far beyond the annotations by detailing the exact statuses returned, the contents of the progress timeline, availability of delivery photo/video flags, and the error message format. Even though readOnlyHint and destructiveHint are already provided, the description adds meaningful behavioral context (e.g., live_tracking_available boolean, payment reference field) that helps an agent anticipate results.

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 well-organized: it starts with the core purpose, provides usage context, lists parameters, and includes a return schema. Every sentence contributes value, and the structure makes it easy to scan. The embedded JSON schema is verbose but justified given the complex return payload.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multiple statuses, nested recipient/items objects, error handling), the description is comprehensive. It explains when to use it, what input to provide, what output to expect, and includes the caveat about order_ref. The annotations and detailed schema round out the context, making the tool fully actionable.

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?

The description's Args section essentially mirrors the input schema, which already contains detailed descriptions for both parameters, including the crucial order_ref distinction. Thus, the description adds little new semantic meaning beyond what the schema provides. The example format ('VIMP34456CB2') is helpful but not a significant increment.

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 uses a specific verb ('Look up') and resource ('status and delivery progress for a Kapruka order by order number'), clearly distinguishing it from sibling tools like kapruka_create_order. It also outlines the exact output, making the purpose unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states when to use the tool ('after a customer has placed and paid for an order and reads back the order number from their confirmation email or the order complete page') and warns against using the order_ref from kapruka_create_order. This provides clear when-to-use and when-not-to-use guidance, effectively differentiating it from related tools.

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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TDQS

A4.7/5.0
Disambiguation5/5

Each tool targets a clearly distinct operation: delivery checking vs city listing, product search vs product fetch, order creation vs tracking, plus an auxiliary card renderer. Even the two delivery-related tools have non-overlapping purposes, and descriptions reinforce the boundary.

Naming Consistency5/5

All tools follow a consistent `kapruka_<verb>_<noun>` snake_case pattern (e.g., check_delivery, create_order, search_products). The verb-noun structure is uniform, making it easy to predict tool names.

Tool Count5/5

8 tools is well-scoped for an e-commerce MCP server, covering catalog browsing, delivery feasibility, order placement, and order tracking without unnecessary bloat. Each tool serves a distinct step in the shopping workflow.

Completeness5/5

The tool surface covers the full agent-visible lifecycle: discover products (search/get/categories), check delivery, create a guest order, and track post-payment status. There are no obvious dead ends for common shopping scenarios.