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Get Global Power

get_global_power
Read-onlyIdempotent

Query global power plant units (operating and pipeline) across all fuels, with capacity, status, coordinates, and owner. Filter by country, fuel, status, or minimum capacity for international energy analysis.

Instructions

Use when a user asks about power plants/units WORLDWIDE or in a NON-US country — operating AND the forward pipeline (announced / pre-construction / under-construction), across ALL fuels (coal, oil/gas, nuclear, solar, wind, hydro, bioenergy, geothermal). Global Energy Monitor Global Integrated Power Tracker: 182,000+ geolocated units across 170+ countries, each with fuel, capacity (MW), status, start year, operator/owner and lat/lng. Filter by country (e.g. Germany, India, Brazil, Japan), fuel (comma-union: coal, oil/gas, nuclear, solar, wind, hydro), status, pipeline=true (JUST the forward set: announced + pre-construction + construction), bbox (minLng,minLat,maxLng,maxLat), or min_mw. Returns a summary (total MW by fuel + count by status) plus the largest units. Try: get_global_power country=India pipeline=true. Do NOT use for US grid telemetry/headroom (use get_grid_intelligence / get_grid_scoreboard) or the US planned-generator feed (use get_power_pipeline) — this is the GLOBAL asset inventory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bboxNoViewport filter as minLng,minLat,maxLng,maxLat
fuelNoFuel/type filter, comma-separated for a union: coal, oil/gas, nuclear, solar, wind, hydro, bioenergy, geothermal
limitNoMax results to return (1-500; default varies by tool)
min_mwNoMinimum unit capacity in MW
statusNoStatus substring filter, e.g. operating, construction, pre-construction, announced
countryNoCountry/area name to filter, e.g. Germany, India, Brazil, Japan
pipelineNotrue = ONLY the forward pipeline (announced + pre-construction + under-construction)

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.
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.
Behavior4/5

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

Annotations already provide readOnlyHint, idempotentHint, destructiveHint. The description adds concrete behavioral details: returns a summary plus largest units, supports specific filter parameters, and includes an example query. This enriches transparency beyond 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?

The description is well-organized: front-loaded with the primary use case, followed by scope, dataset details, filtering options, an example, and clear exclusions. Every sentence serves a purpose without redundancy.

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 the tool's functionality: what it returns (summary + largest units), how to filter (country, fuel, status, pipeline, bbox, min_mw), and an example. An output schema exists but is not needed further; the description is self-sufficient.

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 baseline is 3. The description adds meaningful context for several parameters (e.g., pipeline=true as 'JUST the forward set', fuel as 'comma-union') and explains the filter options in prose. This exceeds the baseline.

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 clearly states the verb ('get') and resource ('power plants/units'), defines the scope ('WORLDWIDE or NON-US country'), and distinguishes it from US-specific sibling tools. It covers both operating and pipeline units across all fuels, making the 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 Guidelines5/5

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

Explicitly states when to use (global/non-US power plant queries) and when not (US grid telemetry, US planned-generator feed), naming alternative tools like get_grid_intelligence and get_power_pipeline. This meets the highest bar for 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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