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Energy profile of an area

energy_profile
Read-onlyIdempotent
Energy composition of an area: EPC band mix, mains gas / electric / oil
split, heat-pump penetration.

`area_id` is the marts area id from `area_resolve` — pass
`analytics_area_id`, not `area_id`, if the resolve response gives both.

Percentages are of properties HOLDING an EPC, not of all stock, and are
whole percentages (0-100). EPCs are lodged on sale or let, so long-held and
social housing are under-represented — say so when reporting a figure.

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

A4.8/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description is free to add real operational context: percentages are of EPC-holding properties only, whole numbers 0-100, EPCs are lodged on sale/let so long-held and social housing are under-represented and the figure should be caveated, plus 'UK only. Free.' That is exactly the kind of bias/cost disclosure annotations cannot carry.

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?

Front-loads the content summary, then the critical parameter routing rule, then the data caveat and scope/cost. Short paragraphs, no filler; every sentence changes how the agent calls or reports the tool.

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 an output schema present, return values need no explanation. The description supplies the remaining gaps an agent needs: input provenance, unit semantics, known coverage bias to caveat in reporting, and geographic/cost scope.

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 description coverage is 0% and the single parameter is undocumented in the schema, so the description must carry it — and it does, explaining the provenance (marts area id from area_resolve) and the exact disambiguation rule (pass analytics_area_id, not area_id, when both exist). No ambiguity remains.

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?

Names a specific resource (energy composition of an area) and enumerates the exact outputs: EPC band mix, mains gas/electric/oil split, heat-pump penetration. That metric list differentiates it from neighbours like area_stock_profile or property_energy_retrofit without needing to name them.

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?

Tells the agent where the required input comes from ('area_id is the marts area id from area_resolve') and which field to pass when both are returned, plus the UK-only scope. It does not, however, name an alternative tool or state when this should be preferred over the other area/energy siblings.

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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