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Get area overview

get_area_overview
Read-onlyIdempotent

One neighbourhood in detail for a decision: local market (sales, turnover, leasehold share, £/m² medians, growth), the borough's official UK HPI (hpi: average price by type, 1/5/10-year change vs London: quote this for how prices moved), £/m² price trend, crime with its offence mix (topTypes, a busy-centre note), road/rail noise, nearby state schools with their standing Ofsted grade plus independent schools (schools.independent), planning rules (home: conservation, Article 4, listed buildings, broadband), council tax bands and a typical bill (councilTax), the IMD decile (deprivation), a ballpark price for a bedroom count and website links.

Input Schema

NameRequiredDescriptionDefault
area_idYesGeography id, e.g. uk:lsoa:E01000951.
bedroomsNoAdds a ballpark price for this size.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds useful provenance context (borough-level 'official UK HPI' vs local market aggregates, a 'busy-centre note' caveat on crime), but says nothing about response size, latency, or cost of a payload that spans a dozen domains.

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?

Compact two-sentence form that opens with the one-line purpose and then enumerates contents, using the parenthetical field names as compact pointers to the output schema rather than prose.

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 restate return shapes, and it still signals domain coverage, data provenance, and the bedroom-price option. The main remaining gap is routing guidance against the many sibling area tools, which the description leaves entirely to the agent.

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 coverage is 100%, so the baseline applies: area_id's LSOA/MSOA/borough pattern is fully documented and the description only echoes that bedroom count yields 'a ballpark price'. It is notable that area_id accepts three geography levels but the description's body text does not discuss how output differs by level.

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 and scope ('One neighbourhood in detail for a decision') and then enumerates the domains returned (market, HPI, crime, schools, planning, council tax, IMD), so an agent knows exactly what the resource covers. It does not name the sibling it is not (get_area_evidence_pack, get_area_metric), so differentiation is inferred from content rather than stated.

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?

Usage is only implied: 'for a decision' and the inline instruction 'quote this for how prices moved' hint at when to reach for the HPI figures, but there is no explicit when-to-use/when-not and no mention of the obvious alternatives like get_area_metric for a single figure or get_area_evidence_pack for a deeper pack.

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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