Renewable Vision energy data

GCC country series

gcc_series

Read-only

Annual country series for Saudi Arabia, the UAE, Oman, Qatar, Kuwait and Bahrain: installed solar, wind and renewable capacity (IRENA, MW); solar and wind generation (TWh), their shares of electricity, demand in total and per person and the carbon intensity of electricity (Our World in Data); CO2 per person, population and renewable share of final energy (World Bank). Each metric carries its publisher, licence and unit; a year not reported is absent, never zero. Narrow by metric, country and years. The country layer of the Energy Atlas, free with membership: it answers a request carrying a member’s API key and refuses one without.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "metric": "<metric>"
    },
    "name": "gcc_series"
  }
}

Input Schema

Name	Required	Description
`to`	No	Last year
`from`	No	First year
`metric`	Yes	One metric, e.g. solar_mw
`country`	No	One country, ISO alpha-2

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnly/closed-world, and the description adds genuinely new behaviour: every metric carries publisher, licence and unit, unreported years are absent rather than zero, and the call requires a member API key and is refused without one. It stops short of describing return shape/pagination in detail, so not a 5.

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?

Three front-loaded sentences with no filler: scope first, then data provenance and the absent-not-zero rule, then the narrowing instruction and the access condition. The membership sentence is slightly verbose but carries real access information.

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?

For a read-only, single-metric-per-call series tool with no output schema, the description covers coverage, provenance, units, missing-data semantics and the authentication requirement. Only the exact response shape is left implicit, which is acceptable given the per-metric metadata disclosure.

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% with enums on metric and country, so the baseline is 3; the description goes further by grouping the enum values into families and attaching source and unit semantics (MW for capacity, TWh for generation, per-capita demand), which the enum strings alone do not convey.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource ('Annual country series'), enumerates the six GCC countries and the metric families, and identifies the three publishers (IRENA, OWID, World Bank), so an agent can tell it returns country-level energy data. It does not explicitly contrast itself with near-neighbour siblings such as gcc_emissions or get_series, which is the only thing keeping it from a 5.

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

Usage Guidelines3/5

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

'Narrow by metric, country and years' tells the agent how to scope a query but not when this tool is the right choice versus gcc_emissions or get_series. The usage context (country layer of the Energy Atlas, member-only) is implied rather than stated as a selection rule.

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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