DOE Energy Information

get_petroleum_data

Get petroleum and oil price or production data from the EIA.

Returns time series data for petroleum products including crude oil prices,
production volumes, imports, exports, and refinery operations.

Args:
    series: EIA series ID for the petroleum data. Common series:
            'PET.RWTC.D' (WTI crude oil daily price),
            'PET.RBRTE.D' (Brent crude oil daily price),
            'PET.EMM_EPMR_PTE_NUS_DPG.W' (US regular gasoline weekly price),
            'PET.MCRFPUS2.M' (US crude oil production monthly).
            Default is 'PET.RWTC.D'.
    limit: Maximum number of records to return (default 100, max 5000).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`series`	No		PET.RWTC.D

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedApr 3, 2026

TDQS

A4.6/5.0

Behavior4/5

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

The description states it 'Returns time series data' and discloses constraints such as default series and maximum limit (5000). With no annotations available, this provides a good but not exhaustive behavioral picture—it doesn't mention API key requirements, rate limits, or error behavior, but the read-only nature is evident.

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 front-loaded with the core purpose, followed by a concise list of parameter details. No redundant or irrelevant sentences exist.

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 combined with the output schema and explicit parameter examples gives a complete picture for using the tool correctly in all common use cases. The sibling context makes the domain boundary obvious.

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?

Even though the input schema has 0% parameter descriptions, the description's Args section fully documents both parameters: series with multiple concrete examples and meaning, and limit with default and maximum. This more than compensates for the schema gap.

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 opens with 'Get petroleum and oil price or production data from the EIA,' which names a specific verb, resource, and data categories. It further enumerates contents (crude oil prices, production, imports, exports, refinery operations), clearly distinguishing it from siblings like get_electricity_data.

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 makes clear this tool is for petroleum/oil data from EIA, so an agent can infer when to choose it over electricity/natural gas tools. It does not explicitly list alternatives or exclusions, but the scope is unambiguous.

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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