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

Annotations already establish that this is read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond those annotations: the data is monthly, organized by sector, and the returned values are expressed in BTU equivalents. It does not discuss pagination or API quirks, but for a read-only data query this is adequately transparent.

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 sentences with no filler: it states the resource, the cadence, the sector options, and the return units. Relevant facts are front-loaded, and every sentence contributes useful information.

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?

For a tool with five optional parameters and no output schema, the description covers the core semantics: monthly frequency, sector dimension, and BTU units. It does not mention the state parameter or date-range behavior, but those are already documented in the schema, so the definition is complete enough for straightforward use.

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 parameters are already well documented in the schema. The description mainly restates the sector enum values and adds no deeper explanation of start/end date handling, state scope, or how the default 'US' rollup works. The description therefore adds only marginal value beyond the schema.

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 identifies the tool as retrieving monthly US energy consumption by sector from EIA, with a clear resource and data domain. It also notes that values are in BTU equivalents. It does not explicitly call out sibling tools like eia_natural_gas or eia_electricity_state, but the 'energy consumption' focus is specific enough to distinguish it from those price/supply-oriented tools.

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 when to use this tool: when monthly US energy consumption data by sector is needed. It gives no explicit guidance about alternatives, such as when to prefer eia_gasoline_prices, eia_natural_gas, or eia_electricity_state instead. The usage context is understandable but not directly contrasted with sibling tools.

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