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UK Carbon Intensity — Regional Breakdown

carbonintensity.energy.regional
Read-onlyIdempotent

Get carbon intensity and generation mix for UK electricity distribution regions. Returns data for all 14–18 UK DNO (Distribution Network Operator) regions, or a single region by region ID (1=North Scotland, 2=South Scotland, 3=North West England, 4=North East England, 5=Yorkshire, 6=North Wales & Mersey, 7=South Wales, 8=West Midlands, 9=East Midlands, 10=East England, 11=South West England, 12=South England, 13=London, 14=South East England). Each region includes forecast intensity in gCO2/kWh, qualitative index, and generation mix percentages. Useful for location-aware carbon-minimising energy decisions. CC BY 4.0, no upstream cost.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
region_idNoUK DNO region ID (1–14 for primary regions, up to 18 for all). Omit to return all regions. 1=North Scotland, 2=South Scotland, 3=North West England, 4=North East England, 5=Yorkshire, 6=North Wales & Mersey, 7=South Wales, 8=West Midlands, 9=East Midlands, 10=East England, 11=South West England, 12=South England, 13=London, 14=South East England

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover readOnlyHint, idempotentHint, openWorldHint, and destructiveHint, so the safety profile is established. The description adds valuable non-schema context: output fields (gCO2/kWh, qualitative index, generation mix), licensing (CC BY 4.0), and cost behavior (no upstream cost).

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?

The main capability is front-loaded, with the region list and use case following naturally. However, the full ID-to-region mapping duplicates the schema, making the description longer than necessary. The licensing and cost note is valuable but the repetition prevents a perfect score.

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?

For a single-optional-parameter, read-only lookup with an output schema, the description provides everything an agent needs: what data is returned, how to scope to a region, and licensing/cost constraints. No critical invocation 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 coverage is 100% and the schema already documents region_id, the valid range, the ID-to-region mapping, and the omit-to-return-all behavior. The description repeats this mapping without adding new semantic meaning, so the baseline score of 3 applies.

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 opens with a specific verb and resource: 'Get carbon intensity and generation mix for UK electricity distribution regions.' It clearly distinguishes itself from sibling tools like carbonintensity.energy.current, forecast, and generation by emphasizing regional DNO scope and optional region_id filtering.

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?

It says the tool is 'useful for location-aware carbon-minimising energy decisions,' which implies a use case, but it never explicitly contrasts with the sibling carbon intensity current/forecast/generation tools or states when not to use this tool. No alternative tool is named.

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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