UK Data for Agents

local_authority_traffic_totals

Read-onlyIdempotent

Gives the total distance driven on all roads in one GB council area each year, in million vehicle miles (and vehicle km), for all motor vehicles and for cars and taxis, plus the area's road length, newest year first. Answers "how much traffic is there in Leeds and is it growing" for council officers, net-zero and carbon plans, and consultants comparing areas. Minor-road traffic is a DfT estimate; this endpoint does not split vans, HGVs or buses (use region_traffic_by_vehicle_type for that at region level). (cost: 1 credit)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "local_authority_traffic_totals"
  }
}

Input Schema

Name	Required	Description
`year`	No	integer, optional, a single year; default is the most recent years
`years`	No	integer, optional, how many recent years when year is not given, 1-40, default 10
`local_authority_id`	No	integer, required, DfT local authority id (from traffic_local_authority_find, e.g. Leeds is 63)

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 5, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so safety is covered; the description adds substantial context beyond them: output units (million vehicle miles and vehicle km), ordering (newest year first), a data-quality caveat that minor-road traffic is a DfT estimate, and a cost of 1 credit. These are exactly the traits an agent needs that structured fields do not carry.

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?

Key facts (what, units, scope, ordering) are front-loaded and every clause carries information — vehicle categories, estimate caveat, sibling routing, credit cost. It is a dense single block with heavy parentheticals, which slightly taxes scanning but wastes no words.

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?

No output schema exists, so the description must explain the return shape, and it does: totals per year for two vehicle groupings plus road length, in stated units, ordered newest first. Combined with the sibling pointer and the DfT-estimate caveat, an agent has everything needed to call this correctly for a 3-parameter read-only tool.

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 year, years and local_authority_id are already fully documented, including the id source and the Leeds=63 example. The description adds only the 'newest year first' ordering hint, which lightly clarifies the default behavior, so the schema still does the heavy lifting and the baseline 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?

States a concrete resource and scope: total distance driven on all roads in one GB council area per year, in million vehicle miles and vehicle km, broken out for all motor vehicles versus cars and taxis, plus road length. This is specific enough that an agent can distinguish it from region_traffic_by_vehicle_type and traffic_local_authority_find 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 Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit use contexts (council officers, net-zero and carbon plans, consultants comparing areas) and names the alternative tool with the exact condition that selects it: vehicle-type splits for vans/HGVs/buses must go to region_traffic_by_vehicle_type. The agent is routed rather than left to infer.

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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