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UK Crimes Near Coordinate

gov.ukpolice.crimes_near
Read-onlyIdempotent

Get street-level crime data within 1 mile of any UK coordinate. Filter by crime category and month, returning location, category, and outcome status.

Instructions

Street-level UK crime records within 1 mile of a coordinate for a given month (England + Wales, 43 forces). Filter by crime category. Returns up to 500 records with category, location, outcome status. OGL v3.0 (commercial OK)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude (e.g. 51.5074 for central London). UK area only.
lngYesLongitude (e.g. -0.1278 for central London).
dateNoMonth in YYYY-MM format (e.g. "2024-06"). Defaults to latest available month if omitted.
categoryNoCrime category slug — "all-crime" (default), "burglary", "violent-crime", "drugs", "robbery", "shoplifting", "vehicle-crime", "anti-social-behaviour", etc.
limitNoMax crime records to return (default 100, max 500).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
Behavior4/5

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

Annotations already indicate safe read-only operation (readOnlyHint, destructiveHint false). The description adds behavioral details: returns up to 500 records, specific output fields (category, location, outcome status), and data license (OGL v3.0 commercial ok). No contradictions with annotations.

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?

Three concise sentences packed with essential information: purpose, scope, parameters, output, license. No unnecessary 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?

The description covers all key aspects: what, where (coordinate, radius, region), when (month), filters, output fields, data source, and licensing. Output schema exists, so return structure details are not needed. Completeness is high given simplicity of the 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 coverage is 100%, so baseline 3. The description adds minimal value beyond schema: it mentions 'filter by crime category' and 'given month' which correspond to the category and date parameters, but schema already describes these. No additional parameter details.

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 clearly states the tool returns street-level UK crime records near a coordinate for a given month, with a specific radius (1 mile), geographic scope (England+Wales, 43 forces), and filter capabilities. It distinguishes from sibling tools like gov.ukpolice.forces and gov.ukpolice.outcomes by focusing on crimes near a point.

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 implies usage for fetching crime records near a coordinate but does not explicitly state when to use vs. alternatives. The context of sibling tools (forces, outcomes) provides implicit guidance, but explicit when-not/alternatives are missing.

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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