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zen-tradings

EIA MCP Server

by zen-tradings

eia_natural_gas_summary

Retrieve natural gas survey summary data from the U.S. Energy Information Administration. Access weekly, monthly, or annual metrics on production, consumption, and market statistics for analysis and reporting.

Instructions

Get natural gas summary data providing an overview of the natural gas survey information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seriesNoData series to retrieve
frequencyNoData frequency
startNoStart period
endNoEnd period
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. It states it 'gets' data (implying a read operation) but doesn't mention authentication requirements, rate limits, error handling, or what format the data returns. For a tool with 5 parameters and no output schema, this leaves significant behavioral gaps unaddressed.

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 a single, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for a data retrieval tool, though it could be slightly more front-loaded with key distinctions from siblings. Every word serves a purpose, earning a high score for conciseness.

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

Completeness3/5

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

Given the tool's moderate complexity (5 parameters, no output schema, no annotations), the description is minimally adequate. It clarifies the tool's purpose but lacks usage guidelines, behavioral details, and output information. With schema coverage at 100%, the description doesn't need to explain parameters, but it should do more to guide the agent on when and how to use this tool effectively.

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%, with all parameters well-documented in the schema itself. The description adds no parameter-specific information beyond implying it retrieves 'summary data' and 'overview' information, which might hint at the 'series' parameter's purpose but doesn't provide additional syntax or format details. This meets the baseline of 3 when schema coverage is high.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'natural gas summary data', specifying it provides 'an overview of the natural gas survey information'. This distinguishes it from siblings like eia_natural_gas_consumption or eia_natural_gas_prices by focusing on summary/overview data rather than specific aspects. However, it doesn't explicitly contrast with all siblings, keeping it at 4 rather than 5.

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 doesn't mention any specific use cases, prerequisites, or comparisons to sibling tools like eia_natural_gas_consumption or eia_natural_gas_production. The agent must infer usage from the tool name and description alone.

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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