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lzinga

US Government Open Data MCP

eia_petroleum

Read-only

Retrieve petroleum prices including crude oil (WTI, Brent), retail gasoline, diesel, and heating oil from EIA. Specify product, frequency, and date range.

Instructions

Get petroleum/oil prices — crude oil spot prices (WTI, Brent), retail gasoline prices, diesel, heating oil.

Product codes:

  • EPCBRENT: Brent crude oil spot price

  • EPCWTI: WTI crude oil spot price

  • EMM_EPMRU_PTE_NUS_DPG: US regular gasoline retail

  • EMM_EPMPU_PTE_NUS_DPG: US premium gasoline retail

  • EMD_EPD2D_PTE_NUS_DPG: US diesel retail

  • EER_EPJK_PF4_RGC_DPG: US jet fuel spot price

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productNoProduct type: 'crude' (default — WTI), 'gasoline', 'diesel', 'all'. Or a specific series ID like 'EPCWTI'
frequencyNoFrequency (default: monthly)
startNoStart date (YYYY-MM or YYYY-MM-DD). Default: 2 years ago
endNoEnd date (YYYY-MM or YYYY-MM-DD). Default: latest available
lengthNoMax rows to return (API max: 5000). Omit to let date range control volume.
offsetNoRow offset for pagination (use with length)
Behavior3/5

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

Annotations declare readOnlyHint=true, and the description uses 'Get', consistent with read-only behavior. The description adds product code details but does not disclose rate limits, authentication needs, or data update frequency beyond what annotations provide.

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 concise, front-loaded with the main purpose, and efficiently lists product codes in a structured manner. Every sentence adds value without redundancy.

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?

Given no output schema, the description adequately explains the types of prices returned. However, it could briefly mention return format or data source to improve completeness for a data retrieval tool.

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?

The input schema has 100% coverage, but the description enriches parameter semantics by explaining specific product codes (e.g., 'EPCWTI' for WTI crude) and their meanings, which is not present in the schema's parameter descriptions.

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 tool retrieves petroleum/oil prices, listing specific types (crude oil spot prices, retail gasoline, diesel, heating oil). It distinguishes itself from sibling EIA tools (e.g., eia_electricity, eia_natural_gas) by focusing on petroleum.

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?

The description implies usage for petroleum price queries but does not explicitly state when to use this tool versus alternatives (e.g., other EIA tools). No exclusion criteria or comparative guidance is provided.

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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