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 what the tool returns ('local utility and their rates ($/kWh)') but does not disclose behavioral traits such as data freshness, rate limits, error conditions, or whether the tool requires authentication. For a tool with no annotation coverage, this leaves significant gaps in understanding its operation.

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 two concise sentences with zero waste. The first sentence states the purpose and scope, and the second specifies the input and output. It is front-loaded and efficiently communicates essential information without unnecessary details.

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 moderate complexity (2 required parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and inputs but lacks details on behavioral aspects (e.g., data sources, limitations) and output structure. Without annotations or an output schema, the agent must infer behavior from the description alone, which is insufficient for full transparency.

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%, with clear descriptions for both parameters (latitude and longitude). The description adds minimal value beyond the schema by reinforcing that these parameters are used to 'get the local utility and their rates,' but does not provide additional semantic context (e.g., coordinate precision, invalid ranges, or examples beyond those in the schema). Baseline 3 is appropriate given 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 with specific verbs ('Get') and resources ('residential, commercial, and industrial electricity rates for any U.S. location'). It distinguishes itself from sibling tools by focusing on utility rates rather than other NREL data (like solar or fuel stations) or unrelated datasets from other agencies.

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 implies usage context by specifying 'for any U.S. location' and requiring latitude/longitude, but does not explicitly state when to use this tool versus alternatives (e.g., other rate calculation tools like 'calc_contract_rates' or 'calc_search_rates'). It provides basic prerequisites but lacks explicit guidance on tool selection.

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