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DC Hub — Data Center & Energy Intelligence

Nearby Infrastructure

get_infrastructure
Read-onlyIdempotent

Discover substations, transmission lines, gas pipelines, and power plants near a location. Get distance, voltage, and capacity for each asset within a configurable radius.

Instructions

Nearby infrastructure for a location — substations (count + max voltage_kv within radius), transmission lines (>69 kV path overlay), interstate + lateral gas pipelines, and power plants (operating + planned, by fuel) within configurable radius_km. Returns distance + capacity for each, joined to HIFLD/EIA. Answers "what is near this parcel", "how far is the nearest substation and what voltage is it". Try: get_infrastructure lat=33.45 lon=-112.07 radius_km=25. Returns raw nearby assets; do NOT use for a single scored site-suitability verdict (use analyze_site).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoCenter latitude in decimal degrees (-90 to 90, required), e.g. 33.45
lngNoAlias for lon — either name works
lonNoCenter longitude in decimal degrees (-180 to 180, required), e.g. -112.07
layerNoOptional single asset layer to return, e.g. substations, transmission, pipelines, power_plants
limitNoMax results to return (1-500; default varies by tool)
latitudeNoAlias for lat — either name works
longitudeNoAlias for lon — either name works
radius_kmNoSearch radius in kilometers around the point, e.g. 25
min_voltage_kvNoOnly include transmission/substations at or above this voltage in kV, e.g. 69

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
quotaNoCaller quota state (remaining calls, tier) when available.
_entityNoPayload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.
citationNoMachine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload. Normally an OBJECT {source, url, license, cite_as, retrieved_at}; a bare string is accepted and carries the attribution line itself.
provenanceNoCollection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.
_front_doorNoIn-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.
_return_loopNoSuggested next-session delta call (get_changes since=24h) so you pull only what changed.
site_evaluation_handoffNoPre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries.
Install Server

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the description adds value by revealing the output nature: raw nearby assets joined to HIFLD/EIA, with distance+capacity per asset. It doesn't contradict annotations and gives useful context about what the tool does with the data.

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?

Dense and front-loaded: the first sentence covers purpose and scope, followed by output details, example questions, an example call, and a guardrail. Slight redundancy with the title, but the structure is efficient and every sentence earns its place.

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?

Combined with the rich input schema and output schema, the description covers the asset layers, return metrics, data provenance, and the key sibling distinction. It doesn't mention default radius_km, but that is delegated to schema annotations and is a minor omission for a tool this well specified.

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%: every property has a description. The description adds a worked example and explains radius_km as configurable, but it does not add per-parameter meaning beyond the schema. Baseline 3 is appropriate 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?

States a specific verb+resource: 'Nearby infrastructure for a location' and enumerates four asset categories with specific metrics (count, max voltage_kv, distance, capacity). It also explicitly distinguishes itself from analyze_site by labeling its output as raw assets rather than a scored verdict.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides a concrete example invocation and a direct exclusion: 'do NOT use for a single scored site-suitability verdict (use analyze_site)'. This routes agents to the correct sibling for scoring while conveying this is the geo-spatial lookup tool.

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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