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Built-stock profile of an area

area_stock_profile
Read-onlyIdempotent
Composition of the built stock in an area: unit counts, HMO share,
mixed-use share, median building height and footprint, solar penetration.

Medians, not means — one tower would skew an average height enough to make
a low-rise district read as mid-rise. Percentages are whole percentages.

`area_id` is the marts area id from `area_resolve`.

UK only. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
area_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already carry the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds genuine value beyond them: medians rather than means and why (skew from towers), whole-percentage output, and 'Free'. Return format is covered by the existing output schema.

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 metric list, then a short methodology note and scope flags; every sentence earns its place. The median aside is slightly conversational but justifies a real methodological choice, so waste is minimal.

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?

With annotations covering safety, an output schema covering return values, and the description covering metric content, methodology, parameter provenance, and geographic scope, an agent has everything needed to select and call this tool 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?

Schema description coverage is 0% for the single parameter, so the description must compensate, and it does: 'area_id is the marts area id from area_resolve' tells the agent both the identifier space and how to obtain a valid value. It could specify format more exactly, but the provenance is the key missing piece and is supplied.

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?

States a specific resource (composition of built stock in an area) and enumerates the exact metrics returned: unit counts, HMO share, mixed-use share, median height/footprint, solar penetration. This enumeration is enough to distinguish it from siblings like area_report or market_profile without opening any schema.

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 prerequisites and scope: area_id comes from area_resolve, and the tool is UK-only. It does not, however, name an explicit alternative or state when not to use it (e.g., versus area_report or energy_profile), so it falls short of full routing 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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