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Infrastructure near a point

infrastructure_at
Read-onlyIdempotent

Find infrastructure near a point, sorted by distance, and filter by type to highlight bridges, towers, or piers amid common street furniture.

Instructions

Infrastructure near a point, nearest first: bridges, towers, piers — and street furniture.

From Overture's base theme (issue #179), type=infrastructure — the
built things that are neither buildings nor POIs. Read the data
honestly before trusting an answer: this layer is dominated by street
furniture (street_lamp, bench, waste_basket, bollard, kerb, crossing),
which outnumbers landmark infrastructure roughly 50:1 in a city
centre. An unfiltered query in a dense area returns lamps and benches
and says nothing about whether a bridge is nearby. To ask about
landmarks, filter: subtype/infra_class match Overture's `subtype` and
`class` columns (case-insensitive substring; infra_class is `class`
under a non-reserved name) — e.g. subtype="bridge", subtype="tower",
subtype="power", infra_class="pier".

Returns {"center", "radius_m", "results": [{"id", "subtype", "class",
"name", "distance_m"}, ...]}, plus "truncated": true, "total_in_range"
and an explanatory "note" whenever more features matched than were
returned. id is the GERS id, usable with other GERS-keyed tools. No raw
geometry (design rule: answers, not data).

Radius search, not containment: most infrastructure is linear or a
bare point, so "what's within radius_m" is the answerable question.
distance_m is measured to the closest point on the feature, not its
centroid — a bridge you are standing on reads ~0 m, not "distance to
the middle of the bridge". radius_m echoes the effective radius, which
may be lower than requested (large values are clamped).

An empty results list is a valid answer, not an error: base-theme
coverage is OSM-derived and patchy, and "no infrastructure within
500 m" is a real finding. Returns a structured {"error": ...} if
upstream is unavailable or the 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
limitNo
subtypeNo
radius_mNo
infra_classNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the bar is about added context. The description adds substantial behavioral detail: radius clamping, distance measured to closest point rather than centroid, empty results as a valid answer, truncation/note behavior, GERS id semantics, no raw geometry, and structured error cases.

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 long but organized into purposeful paragraphs: summary, data caveat, filtering guidance, output shape, radius behavior, and error handling. It is front-loaded with the primary purpose and uses examples compactly. Some phrasing could be trimmed, but nothing is merely filler.

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 is complete for a tool of this complexity: it explains what the tool returns, the truncated/total_in_range/note mechanics, how distance_m is computed, radius clamping, valid empty results, and error responses. The output schema and annotations cover the structured contract, while the description fills the practical gaps an agent would need.

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

Parameters4/5

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

With 0% schema description coverage, the description carries the semantic burden. It thoroughly explains subtype and infra_class as case-insensitive substring matches against Overture columns, and meaningfully describes radius_m effective behavior. It does not explicitly explain lat/lon units or the limit parameter semantics beyond the default, though these are more self-evident.

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 states a clear, specific function: return infrastructure near a point, nearest first, with named categories (bridges, towers, piers, street furniture). It differentiates itself from siblings by specifying this is Overture type=infrastructure — built things that are neither buildings nor POIs, which separates it from tools like buildings_at.

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 gives strong guidance on when to use it and how to frame queries, including the crucial warning that unfiltered results are dominated by street furniture and the recommendation to filter by subtype/infra_class for landmark questions. It does not explicitly name alternative tools for when this tool should not be used, so it stops short of a full 5.

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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