US Government Open Data MCP

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

No annotations are provided, so the description carries the full burden. It mentions data types and sectors but fails to disclose critical behavioral traits such as rate limits, authentication needs, data freshness, or error handling. For a tool with 8 parameters and no output schema, this lack of behavioral context is a significant gap.

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 sized and front-loaded, with the core purpose stated first followed by brief details on sectors and data types. It avoids unnecessary fluff, but could be slightly more structured (e.g., bullet points for clarity). Overall, it is efficient with minimal waste.

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 (8 parameters, no annotations, no output schema), the description is incomplete. It lacks information on return values, error cases, data sources, or usage examples. While it covers basic purpose and parameters, it does not provide enough context for effective tool invocation in a broader workflow.

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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds some value by listing sectors and data types, which aligns with the schema's enum values, but does not provide additional semantic context beyond what the schema offers. This meets the baseline for high schema coverage.

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 electricity retail prices, generation, or consumption by state and sector.' It specifies the resource (electricity data) and action (get/retrieve). However, it does not explicitly distinguish this tool from its sibling tools (e.g., eia_natural_gas, eia_petroleum), which are also EIA data tools but for different energy types, so it misses full sibling differentiation.

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. It lists sectors and data types but does not mention sibling tools (e.g., eia_natural_gas for gas data) or any context for selection. There is no explicit when/when-not or alternative tool naming, leaving usage unclear.

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