US Government Open Data MCP

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 mentions what data is available but doesn't describe how the tool behaves: no information about rate limits, authentication requirements, data freshness, error handling, or response format. The description is purely about data content, not tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise and front-loaded: the first sentence clearly states the purpose, followed by a useful list of product codes. There's no wasted text, though it could be slightly more structured (e.g., separating purpose from examples).

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

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

Given the tool's complexity (6 parameters, no output schema, no annotations), the description is minimally adequate. It covers what data is available but lacks crucial context about how to use the tool effectively, what to expect in return, and behavioral characteristics. The product code list is helpful but doesn't compensate for missing behavioral and usage guidance.

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

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

The schema has 100% description coverage, so parameters are well-documented in the schema itself. The description adds value by listing specific product codes (EPCBRENT, EPCWTI, etc.) which helps users understand valid 'product' values beyond what the schema's description mentions. However, it doesn't provide additional context about parameter interactions or usage patterns.

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

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

The description clearly states the tool's purpose: 'Get petroleum/oil prices' with specific examples of price types (crude oil spot prices, retail gasoline, diesel, heating oil). It distinguishes itself from sibling tools by focusing on petroleum data, but doesn't explicitly contrast with alternatives like 'eia_electricity' or 'eia_natural_gas' beyond the subject matter.

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

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. While it lists product codes, it doesn't mention when to choose this over other EIA tools (e.g., eia_electricity for electricity data) or other data sources. There's no context about prerequisites, limitations, or typical use cases.

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