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Listing Location Toolkit

by io.github.Nero-Engine
OverviewDiscussionsAdmin

Schools near an address

schools_nearby
Read-onlyIdempotent

Nearest schools by level (primary, middle, secondary, private, special, nursery) with miles, walk and drive minutes. England: every open school from the DfE register with the latest Ofsted grade or report card, type, ages, pupils, gender, faith and selective flag. US: every public school from NCES 2024-25 (grades, pupils, pupils per teacher, charter, free lunch share, district) and private schools, plus the school district the address is in from Census boundaries, with in_your_school_district on each public school. Wales, Scotland and NI: OpenStreetMap schools. Explains how catchments and admissions work for the address. There is no national catchment map in the UK or US: the answer says who decides.

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": "schools_nearby"
  }
}

Input Schema

NameRequiredDescriptionDefault
latNoLatitude in decimal degrees (use with lon instead of address).
lonNoLongitude in decimal degrees.
levelsNoDefault primary, middle, secondary, private.
addressNoStreet address with town and ZIP or postcode, e.g. "7090 State Highway 80, Cooperstown, NY 13326" or "Ambleside LA22 9BB". Not needed when lat and lon are given.
countryNoOptional hint for the address lookup.
max_milesNoFurthest school to list. Default 10, max 25.
per_levelNoSchools per level. Default 3 to 5, max 10.
drive_minutesNoAdd drive minutes (one router call). Default true.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already establish a safe, idempotent, open-world read, so the description is free to add coverage caveats: English schools come only from the open DfE register, Welsh/Scottish/NI results are OSM-only (much thinner), and drive minutes cost 'one router call'. Those regional quality differences and the explicit statement that no national catchment map exists are exactly the kind of behavioral context 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core capability, then organized by country in rough order of data richness. Sentences are information-dense rather than padded, though the region rundown reads as one long crowded paragraph that could be split or trimmed of a few field enumerations.

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 8 parameters, multi-source data and no output schema, the description does the necessary work: it says what each result contains per country, that public schools carry in_your_school_district, and that catchment/admissions questions are answered qualitatively. Only minor gaps remain, such as pagination or how results are ordered within a level.

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 lat/lon vs address, level enums, max_miles and per_level defaults are all documented in the schema already. The description adds little syntax-level meaning beyond reiterating the level taxonomy and implying drive_minutes drives the router call; baseline 3 applies when the schema does the heavy lifting.

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?

Opens with a specific verb-plus-resource and scope: nearest schools by level with distance, walk and drive minutes. The per-country data provenance (DfE/Ofsted for England, NCES 2024-25 for the US, OSM for Wales/Scotland/NI) makes it unmistakable versus siblings like area_profile or daily_needs.

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: an agent can infer this is the tool for 'schools around an address', but no sibling is named and there is no explicit when-not-to-use. The one routing-like statement ('There is no national catchment map in the UK or US: the answer says who decides') sets expectations for the answer rather than guiding tool selection.

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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