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DC Hub — Data Center & Energy Intelligence

Renewable Energy

get_renewable_energy
Read-onlyIdempotent

Retrieve US state renewable-energy capacity, fuel mix, and top projects to size PPAs or site data centers. Add state and coordinates for nearest projects within 50 miles.

Instructions

FRONT DOOR CHECK — if the question pairs renewables with siting, grid headroom or a market shortlist ("where can I put a 24-7-CFE campus"), call execute_plan(intent="<the user's question, unchanged>") instead. If you want one state's renewable fuel mix or PPA sizing input on its own, get_renewable_energy IS the right call — one round trip, and routing it through the planner would only cost steps. Use when siting a renewable-powered data center, sizing a PPA, reading one US state's utility-scale fuel mix, or assessing RE100/24-7-CFE feasibility. Example: "What is Texas wind+solar capacity and how much utility-scale solar is operating today?" — get_renewable_energy energy_type=solar state=TX. Params: energy_type one of "solar" | "wind" | "combined" (omit for all); state 2-letter US code (e.g. TX, VA, AZ); lat+lon (optional) for the nearest projects within 50mi. Returns: {capacity_mw_total, by_fuel: {solar_utility, solar_rooftop, wind_onshore, wind_offshore}, capacity_factor_pct, top_projects[{name, mw, operator, cod}], state_rps_target_pct, source: "EIA-860 + state RPS"}. Do NOT use for live grid generation (use get_grid_data) or non-US (use get_grid_scoreboard for EU/UK/AU/TW).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoOptional latitude in decimal degrees (-90 to 90) to find nearest projects within 50mi
lngNoAlias for lon — either name works
lonNoOptional longitude in decimal degrees (-180 to 180) to find nearest projects within 50mi
stateNoUS state abbreviation, e.g. TX, VA, AZ
latitudeNoAlias for lat — either name works
longitudeNoAlias for lon — either name works
energy_typeNoRenewable type: "solar", "wind", or "combined"; omit for all

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

A4.4/5.0
Behavior4/5

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

Annotations already cover readOnly, idempotent, and non-destructive behavior, so the description does not need to repeat those. It adds useful context: one round trip, source EIA-860 + state RPS, the 50-mile radius behavior for lat/lon, and the exact returned shape. This is strong supplementary disclosure beyond the annotations.

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 dense and front-loaded with the routing decision, followed by use cases, an example, return fields, and exclusions. Everything earns its place, though the 'one round trip' and 'routing it through the planner would only cost steps' points are slightly redundant.

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 fully covers when to use, when not to use, example parameter usage, return structure, data source, and sibling alternatives. With no required parameters and a complete input schema, nothing essential is missing for an agent to call this tool correctly.

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 the baseline is 3. The description mostly restates what the schema already says: energy_type values, 2-letter state code, and optional lat/lon for nearest projects within 50 miles. The worked example adds minor interpretive value but no real new semantic layer.

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 names a specific resource and verb: retrieving one US state's renewable fuel mix, capacity, capacity factor, top projects, and RPS target. It clearly distinguishes itself from execute_plan, get_grid_data, and get_grid_scoreboard, so an agent can identify the intended call without opening the schema.

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?

Explicit guidance is included: use for siting, PPA sizing, state fuel mix, and RE100/24-7-CFE feasibility; do not use for live grid generation (get_grid_data) or non-US regions (get_grid_scoreboard). It also warns against routing through execute_plan when a direct call is cheaper, giving clear when/when-not advice.

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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