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UK Property Intelligence

rental_analysis

Rental market analysis for a UK postcode.

Returns median/average rent, listing count, and rent range. Optionally calculates gross yield from a given purchase price. Auto-escalates search radius if local listings are sparse (thin market).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
radiusNoSearch radius in miles (default 0.5)
postcodeYesUK postcode (e.g. "NG1 1AA")
auto_escalateNoWiden radius if fewer than 3 listings found (default true)
building_typeNoFilter by building type: F=flat, D=detached, S=semi, T=terraced (default all)
purchase_priceNoOptional purchase price to calculate gross yield

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "additionalProperties": true,
      +  "type": "object"
      +}
  4. First observed

TDQS

A4/5.0
Behavior3/5

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

Without annotations, the description carries the full burden for behavioral transparency. It discloses the auto-escalation of search radius for thin markets, a valuable behavioral trait. However, it omits other context such as data sources, failure modes, or potential variability in listings, leaving room for improvement.

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 three sentences, front-loaded with purpose. The first sentence defines the tool, the second lists return values, and the third explains a key behavior. Every sentence is informative, with no fluff.

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 an output schema present, the description needn't detail return structures. It covers the core purpose, optional yield calculation, and auto-escalation behavior. For a moderate 5-parameter tool, this is largely complete, though it misses data source or recency context that would round it out.

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 baseline is 3. The description adds minimal semantic value beyond the schema, merely restating purchase_price for gross yield and auto_escalate for thin markets, which the schema already covers in more detail.

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 starts with a specific verb+resource: 'Rental market analysis for a UK postcode'. It clearly defines the output (median/average rent, listing count, rent range) and distinguishes itself from sibling tools like property_yield by focusing on rental metrics.

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 gives clear context: use this tool for rental market analysis in a UK postcode. It does not explicitly name alternative tools, but the domain is obvious. No exclusions are stated, which aligns with a 4 rather than a 5.

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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