DOE Energy Information

get_electricity_data

Get electricity generation, consumption, or price data from the EIA.

Returns data on electricity production, retail sales, prices, and fuel
consumption for power generation across US states and sectors.

Args:
    state: Two-letter US state abbreviation (e.g. 'CA', 'TX'). Omit for national data.
    sector: Sector filter. Common values: 'RES' (residential), 'COM' (commercial),
            'IND' (industrial), 'TRA' (transportation), 'ALL' (all sectors).
    frequency: Data frequency: 'monthly', 'quarterly', or 'annual'. Default is 'monthly'.
    limit: Maximum number of records to return (default 100, max 5000).

Input Schema

TableJSON Schema

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

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.4/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It states that the tool returns data and lists the data categories, but it does not disclose potential rate limits, authentication requirements, or behavior on invalid inputs. This is adequate but minimal for a read-only data retrieval tool.

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 efficiently structured: a one-sentence purpose followed by a clear Args section. Every sentence adds value, and the parameter list is formatted for easy scanning.

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?

With an output schema present and four optional parameters, the description fully covers the necessary usage context. It explains the data source, parameter semantics, and return scope. No critical information is missing for a simple data retrieval 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?

The schema has 0% description coverage, but the description comprehensively explains all four parameters: state with examples, sector with common values, frequency with options and default, and limit with default and max. This fully compensates for the schema's lack of detail.

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 electricity generation, consumption, or price data from the EIA, with specific data types (production, retail sales, prices, fuel consumption). It is distinct from sibling tools which target natural gas and petroleum, so the resource is unambiguous.

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 gives clear context that this is for electricity data from EIA and provides parameter usage examples. However, it does not explicitly state when not to use it or name alternative sibling tools, relying on the sibling tool names to imply the distinction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All DOE Energy Information tools Inspect

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TDQS

A4.4/5.0

Disambiguation5/5

Each tool targets a distinct energy domain: electricity, natural gas, petroleum, and statewide profiles. No overlap in purpose, and the state profile provides a broader but clearly separate function.

Naming Consistency4/5

Three tools follow the pattern get_<fuel>_data, while get_state_energy_profile deviates slightly by not ending in _data. Overall the naming is consistent with a get_ prefix and clear resource identifiers.

Tool Count5/5

Four tools is a well-scoped set for an energy data server, covering major fuel types plus a comprehensive state view. Each tool serves a distinct purpose without redundancy.

Completeness4/5

The server covers electricity, natural gas, petroleum, and state-level profiles, which covers core energy data needs. Missing explicit coal or renewable endpoints, but these may be secondary given the state profile provides cross-fuel data.

Resources

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