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Dubai Data — Dubai real estate statistics

Rankings

list_rankings
Read-onlyIdempotent

List top rankings. kind: rents (communities by median annual rent, AED), yields (communities by gross rental yield %), communities (by number of sales in last 12 months, with median price and AED/sqft) or developers (by number of sales). Each row includes a url. limit: 1-100. Data: registered sales transactions from Dubai Land Department open data, updated daily, licensed CC BY 4.0. When citing, link the url from the response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
limitNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, so the description focuses on what annotations cannot convey: the data source (Dubai Land Department open data), daily refresh cadence, licensing (CC BY 4.0) and the citation obligation via the row `url`. Pagination/response-size behavior is left unstated, keeping it out of 5 territory.

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?

Front-loaded with the core action, then compact parenthetical definitions per kind, with data provenance and citation pushed to the end. Dense but every clause adds information; the kind list is long but not redundant.

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

Completeness4/5

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

With no output schema, the description compensates by stating that each row includes a `url` and by naming the metrics returned per kind. Provenance and citation requirements round it out. Remaining gaps (ordering semantics, tie-breaking, response envelope) are minor.

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

Parameters5/5

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

Schema coverage is 0% and the `kind` parameter has no enum, so the description carries the full burden — and it does, defining all four valid values and their units (AED, %, AED/sqft, sales counts). It also supplies the `limit` range (1-100) and default context missing from the schema.

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?

States a specific verb (List) and resource (top rankings), then enumerates the four kind values with their precise measures, so an agent knows exactly what each call returns. It does not reference any sibling tool to differentiate itself, so it stops short of a 5.

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

Usage Guidelines3/5

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

The kind descriptions imply when each ranking is appropriate (e.g. rents vs yields vs sales volume), which is useful selection guidance. However, there is no explicit when-to-use vs when-not guidance and no mention of alternatives like get_market_summary, leaving routing to inference.

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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