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Evlek — Northern Cyprus Property MCP Server

Illustrative Student-Housing Rental Scenario

student_housing
Read-only

Calculate one illustrative student-rent scenario from caller-supplied monthly rent and occupied months. The university only supplies location context; no Evlek rent or occupancy baseline, observed demand/income, forecast, guarantee, or advice is used.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
universityYesUniversity name, short code, or known alias, matched against the canonical Evlek university catalog.
purchasePriceNoOptional purchase price in GBP (enables yield).
monthlyRentGBPYesUser-supplied monthly long-term rent assumption in GBP.
occupiedMonthsYesUser-supplied number of occupied and paid months in the 12-month scenario period.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYes
dataSourceYes
universityYes
assumptionsNo
estimateTypeNo
monthlyRentGBPYes
occupiedMonthsNo
grossRentToPricePctNo
usesLiveListingDataNo
modelledGrossRentGBPNo

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, which the description does not contradict. It adds value by clarifying that the output is illustrative and that the tool does not use or imply any baseline data, forecast, or advice, setting expectations about the limited scope and nature of the calculation.

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 compact, two sentences long, with the primary action and key inputs in the first sentence. It front-loads the core purpose and adds a clarifying limitation in the second, with no wasted words.

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 simplicity, the presence of an output schema, and annotations, the description sufficiently covers the essential context. It explains the illustrative nature and what inputs are used, while the schema and output schema handle parameter and return details. No critical information is missing.

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. The description mentions 'caller-supplied monthly rent and occupied months' but adds no additional meaning beyond what the schema provides. It does not discuss the optional purchasePrice, leaving the schema to carry that information.

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 states a specific verb and resource: 'Calculate one illustrative student-rent scenario from caller-supplied monthly rent and occupied months.' This clearly distinguishes it from sibling tools that retrieve listings or price indices, as it is a calculation tool with a specific, narrow purpose.

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?

The description provides clear context: this tool is for an illustrative scenario, not a forecast, and explicitly states that no Evlek baseline, demand/income, guarantee, or advice is used. However, it does not explicitly name alternative tools for when a forecast or more detailed analysis is needed, so it stops short of full usage guidance.

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

A3.9/5.0
Disambiguation2/5

Several tools have overlapping purposes: fetch and get_listing_detail both return full listing details (differing only by ID type), and search and search_listings both perform listing searches (differing by query style). The payment_plan tool is misleadingly named as it only converts currency, not plan payments.

Naming Consistency3/5

Most tools follow a verb_noun pattern (compare_cities, get_listing_detail, search_listings), but exceptions like fetch, search, payment_plan, and student_housing break the pattern. The mix is readable but not fully consistent.

Tool Count4/5

14 tools is within the typical well-scoped range, but the set includes redundant pairs (fetch/get_listing_detail and search/search_listings) that could be consolidated, making it feel slightly inflated for the actual functionality.

Completeness4/5

The server covers core discovery (search, get detail), aggregate pricing (index, district, city comparisons), and specialized calculations (yield, student housing). As a read-only property search server it is fairly complete, though it lacks explicit filter/list-by-type tools beyond search_listings.