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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description does not need to repeat those safety guarantees. It adds meaningful behavioral context beyond annotations by explaining the cadence of each series (daily, monthly, weekly) and the default selection of 'spot', which informs how start/end parameters should be formatted.

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 extremely efficient: two sentences cover the data source, all four series options with their meanings, and the default. The most important identifying information is front-loaded, and there is no redundant wording or filler.

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 read-only data-query tool with a well-defined schema and comprehensive annotations, the description covers the key information an agent needs: the data source, the series choices, their cadences, and the default. It omits details like units or exact output fields, but given the absence of an output schema and the simplicity of the tool, this is not a significant gap.

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 baseline is 3, but the description adds semantic value by defining what each series enum actually measures (Henry Hub daily, NYMEX front-month, monthly retail, weekly storage). This helps the agent understand which enum to select and also supplements the start/end date formatting guidance by clarifying cadence.

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 a provider of US natural gas data from EIA and enumerates the four series options with their granularity and meaning. It lacks an explicit verb like 'retrieve' or 'query', but it is specific enough that an agent can distinguish it from other EIA sibling tools such as eia_oil_supply or eia_electricity_state.

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 explaining what each series represents and noting the default, which helps an agent choose among the series options. However, it does not explicitly state when to prefer this tool over sibling EIA tools, nor does it mention any exclusions or alternatives. The guidance is useful but largely implicit.

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