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kapruka_list_delivery_cities

Read-onlyIdempotent

List or search Sri Lankan cities Kapruka delivers to.

Use the `query` param to filter (e.g. "colombo" → all Colombo zones,
"anur" → Anuradhapura). Without a query you get the first 25 cities
alphabetically, which is rarely what an agent needs — pass a query.

Returns canonical city names (use these as the `city` argument to
kapruka_check_delivery) plus any common aliases / vernacular spellings.

Args:
    params (ListDeliveryCitiesInput):
        - query (Optional[str]): Partial match filter
        - limit (int): Max results, 1–50 (default 25)
        - response_format (str): 'markdown' (default) or 'json'

Returns:
    str: Cities list in the requested format.

    JSON schema:
    {
      "cities": [{"name": str, "aliases": [str]}],
      "total_matched": int,
      "showing": int
    }

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?

Adds substantial behavioral detail beyond annotations: default shows first 25 cities alphabetically, query enables partial case-insensitive match, response_format can be markdown or json, and returns canonical names plus aliases. The caveat about the default being rarely needed is honest and useful.

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?

Well-structured and front-loaded: opening purpose, usage guidance, Args section, and Returns with JSON schema. Each sentence contributes relevant information without unnecessary verbosity.

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 list/search functionality and available output schema, the description covers default behavior, filtering, response formats, and return structure. It even includes a JSON schema excerpt, making it complete for an agent to call correctly.

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

Parameters4/5

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

The description restates parameter names and types, but also adds illustrative examples and meaning beyond the schema. It explains the query behavior with concrete examples and clarifies that returned names should be used as the `city` argument, enriching parameter semantics.

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?

Clearly states it lists or searches Sri Lankan cities Kapruka delivers to, with a specific verb (list/search) and resource (cities). It distinguishes from sibling kapruka_check_delivery by noting it returns canonical city names to use as the `city` argument for that tool.

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

Usage Guidelines4/5

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

Provides explicit usage guidance: warns that without a query the default alphabetical limit is rarely what an agent needs, and gives example filters ('colombo' → Colombo zones, 'anur' → Anuradhapura). It implies the relationship to kapruka_check_delivery but does not state when to avoid using this tool.

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.