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Land use at a point

land_use_at
Read-onlyIdempotent

Identify land use and land cover at a coordinate. Returns Overture classifications (subtype, class, name) for the most specific polygon when multiple overlap; null when no coverage.

Instructions

What kind of land is this: land use and land cover classification at a point.

From Overture's base theme (issue #167) — PlaceRoot's first tool over
base, distinct from the place-search and area-summary tools (those cover
discrete POIs, not the land itself). Returns {"lat", "lon", "land_use":
{"subtype", "class", "name"} or null, "land_cover": {"subtype",
"class"} or null}. No raw geometry (design rule: answers, not data).

null for either field means no polygon of that type covers the point —
coverage is OSM-derived and patchy outside well-mapped cities, so this
is a common, valid answer for a rural or remote point, not an error.
When multiple polygons overlap (Overture nests them, e.g. a park inside
a residential parcel), the smallest/most specific one is returned and
a "note" flags that the pick was made among several valid candidates.
Returns a structured {"error": ...} if upstream is unavailable or a
base-theme dataset is missing geometry/bbox, and {"error":
"bad_request"} for a non-finite or out-of-range coordinate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lonYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations, the description richly documents null semantics, patchy OSM coverage, overlapping-polygon resolution, the 'note' flag, and structured error cases for upstream failures and bad coordinates. This is exactly the behavioral context an agent needs that annotations cannot provide.

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?

Although long, every sentence earns its place: purpose, output shape, null meaning, overlap behavior, and error semantics are all covered without redundancy. The most important scoping information appears early.

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?

Given the tool's moderate complexity, the description covers the response shape, valid null cases, overlap selection logic, and failure modes. An agent has enough information to invoke it correctly and interpret results, especially with the output schema also present.

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?

The schema only exposes lat/lon as numbers with zero description coverage. The tool description adds minimal parameter-specific meaning beyond mentioning out-of-range coordinates as an error case; the parameter names are self-evident, but coordinate system and range details are not explicitly documented.

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 clear question-answer framing ('What kind of land is this') and explicitly identifies the resource as land use and land cover classification at a point. It also distinguishes itself from place-search and area-summary tools, making its purpose unmistakable.

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 clearly states the tool is for querying land itself, not discrete POIs, and names the broad tool categories it is distinct from. However, it does not explicitly contrast with point-query siblings like infrastructure_at or buildings_at, so an agent could use more direct exclusion criteria.

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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