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chrischall

onehome-mcp

by chrischall

Local-Logic primary + high schools near a lat/lng

onehome_get_schools
Read-onlyIdempotent

Fetches primary and high-school data for a coordinate, including attributes and proximity distances. Use it to check schools around a property.

Instructions

Fetch the Local-Logic school data for a coordinate — separate primary and high-school lists, each entry with name, attributes (types/grades/programs/levels), and proximity (walking distance + straight-line distance). Returns an error field with HTTP details if the consumer session does not have access (the schools endpoint is sometimes agent-only). lat/lng usually come from onehome_get_property (latitude / longitude).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lngYes
languageNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observedv0.13.1

TDQS

A3.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds critical behavioral context: an error field with HTTP details when access is denied, the endpoint being sometimes agent-only, and the response structure. This goes beyond what annotations provide and is highly transparent.

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 description is three sentences, front-loaded with the core purpose, and includes essential context (error handling, source of lat/lng). It is efficient without unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description adequately describes the return structure (lists, attributes, proximity) and error behavior. However, it omits explanation of the optional 'language' parameter and leaves 'attributes' vague. For a tool with 3 parameters and no output schema, this is moderately complete but not fully.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It explains lat/lng as coordinates and mentions they usually come from onehome_get_property, but does not describe units, ranges, or the optional 'language' parameter at all. This leaves significant gaps in parameter understanding.

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 verb 'Fetch' and the resource 'Local-Logic school data for a coordinate', and specifies the output structure (separate primary and high-school lists with name, attributes, and proximity). It differentiates from siblings by noting the lat/lng source from onehome_get_property, establishing a distinct workflow.

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?

The description provides context on typical input (lat/lng from onehome_get_property) but does not explicitly state when to use this tool over alternatives like onehome_get_walk_score or search tools. It implies usage but lacks clear when-to-use and when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.