DOE Energy Information

get_natural_gas_data

Get natural gas production, consumption, or price data from the EIA.

Returns data on natural gas wellhead prices, marketed production, consumption
by sector, and interstate pipeline flows.

Args:
    state: Two-letter US state abbreviation (e.g. 'TX', 'PA'). Omit for national data.
    frequency: Data frequency: 'monthly' or 'annual'. Default is 'monthly'.
    limit: Maximum number of records to return (default 100, max 5000).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_natural_gas_data"
  }
}

Input Schema

Name	Required	Default
`limit`	No
`state`	No
`frequency`	No	monthly

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedApr 3, 2026

TDQS

A4.3/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses return data categories and parameter constraints (max limit, default frequency, optional state). However, it omits behavioral details like authentication, error handling, or data ordering. The max limit and national-state default are useful, but more transparency would be expected.

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 efficient and well-structured: a purpose sentence, a data-category sentence, and a clean Args list. No filler or redundancy; every sentence contributes.

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?

The description covers the core purpose, data types, and all parameters with constraints. An output schema exists, so return values need not be explained. It could mention the US scope explicitly, but 'from the EIA' implies it. Overall, it is sufficiently complete for a simple query tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description fully compensates. It explains each parameter: state (two-letter abbreviation, omit for national), frequency (monthly/annual, default), and limit (default and max). This adds significant meaning beyond the bare schema types and defaults.

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 'Get natural gas production, consumption, or price data from the EIA' with a specific verb and resource. It enumerates the data categories (wellhead prices, marketed production, consumption by sector, pipeline flows), distinguishing it from sibling tools for electricity, petroleum, and state energy profiles.

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

Usage Guidelines4/5

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

The description implies usage by specifying the exact natural gas data categories available, making it clear when to use this tool over siblings. It does not explicitly name alternatives or provide exclusion criteria, but the context is unambiguous given sibling names.

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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