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DC Hub — Data Center & Energy Intelligence

Renewable Energy

get_renewable_energy
Read-onlyIdempotent

Retrieve utility-scale solar/wind capacity, capacity factors, top projects, and RPS targets for a U.S. state to size PPAs, assess renewable feasibility, or find nearby projects for data center siting.

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.
Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive, so the bar is lower, but the description adds valuable behavioral context: it returns data sourced from EIA-860 + state RPS, takes one round trip, and would add steps if routed through the planner. No contradiction with annotations.

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?

Long but densely informative, with clear structural separation: routing check, use cases, example, parameter summary, return shape, and exclusions. Every sentence earns its place; the structure makes it easy for an agent to quickly locate the information needed.

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 complexity (7 params, output schema, interactions with sibling tools), the description covers all necessary aspects: purpose, alternatives, parameter usage, return structure, data source, and restrictions. An agent has everything needed to select and invoke this tool correctly.

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?

Schema coverage is 100%, so the baseline is 3. The description goes beyond the schema by giving a fully worked example call ('get_renewable_energy energy_type=solar state=TX') and clarifying the 'omit for all' semantics for energy_type, plus reinforcing the 50-mile radius for lat/lon. The added example aids correct invocation.

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 explicitly states this tool retrieves renewable energy data for one US state, with a specific verb ('get') and resource ('renewable fuel mix', 'PPA sizing input'). It distinguishes itself from sibling tools like execute_plan by explaining exactly when get_renewable_energy is the right call versus when to defer to the planner.

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?

The description provides a clear 'FRONT DOOR CHECK' telling the agent when to call execute_plan instead, gives the specific use cases (siting, PPA sizing, RE100 feasibility), and ends with explicit Do NOT use conditions naming alternative tools (get_grid_data, get_grid_scoreboard). This is textbook when-to-use/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.

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