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zen-tradings

EIA MCP Server

by zen-tradings

eia_electricity_operational_data

Retrieve U.S. electricity operational data including generation, fuel consumption, and emissions by state, sector, and energy source for analysis and reporting.

Instructions

Get monthly and annual electric power operational data including generation, fuel consumption, and emissions by state, sector, and energy source. Source: Form EIA-923

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNoState code (e.g., 'CA', 'TX')
fuel_typeNoFuel type code (e.g., 'NG' for natural gas, 'COL' for coal, 'NUC' for nuclear, 'SUN' for solar, 'WND' for wind)
frequencyNoData frequency
startNoStart date
endNoEnd date
data_columnsNoData columns to retrieve (e.g., 'generation', 'total-consumption')
limitNoMaximum number of records (default: 100)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It mentions the data source but does not cover critical aspects like rate limits, authentication needs, error handling, or response format, which are essential for a tool with 7 parameters and no output schema.

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?

The description is concise and front-loaded, efficiently stating the tool's purpose in a single sentence without unnecessary details. However, it could be slightly improved by including brief usage context to enhance clarity without sacrificing brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters, no output schema, and no annotations), the description is incomplete. It lacks information on behavioral traits, response structure, and usage guidelines, making it insufficient for an agent to fully understand how to invoke and interpret results from this tool.

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

Parameters3/5

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

The schema description coverage is 100%, so the schema fully documents all 7 parameters. The description adds no additional parameter semantics beyond what the schema provides, such as clarifying relationships between parameters or usage examples, meeting the baseline score for high schema coverage.

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's purpose with specific verbs ('Get') and resources ('monthly and annual electric power operational data'), and distinguishes it from siblings by specifying the data source ('Form EIA-923') and content scope ('generation, fuel consumption, and emissions by state, sector, and energy source'), unlike sibling tools that focus on different aspects like facility fuel, capacity, or retail sales.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools or specify contexts where this tool is preferred, such as for operational metrics versus capacity or sales data, leaving the agent without explicit usage direction.

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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